ambicuity/Awesome-MICCAI-2026

# Awesome MICCAI 2026 [](https://awesome.re) This repository automatically discovers and organizes MICCAI papers from arXiv that include public code links. A daily bot run searches arXiv metadata, validates links and formatting, assigns categories with confidence tiers, and regenerates the list deterministically. ## 📋 Table of Contents ## ✅ Inclusion Policy - The source of truth is arXiv metadata (`title`, `abstract`, and `comment`) plus public repository links. - Papers must include MICCAI wording in searchable arXiv metadata; when scope is `miccai-2026`, entries must indicate 2026. - Code links must resolve to supported public hosts: GitHub, GitLab, or Hugging Face. - A paper may appear in multiple categories intentionally when it strongly matches multiple tasks. ## 🔍 Trust and Validation - Content between `` and `` markers is bot-generated and overwritten on each successful run. - Daily automation fails fast if discovery is incomplete, generated markdown is malformed, or quality checks fail. - README validation checks marker integrity, malformed URLs, duplicate entries per category, and unsupported code hosts. - Default automation runs with `--conference-scope miccai-all-years --mode broad --tracks all`. - Maintainers can narrow scope with `--conference-scope miccai-2026` and stricter matching via `--mode strict`. ## 📈 Coverage Report - Conference scope: `miccai-all-years` - Discovery mode: `broad` - Tracks: `all` - Total code-backed papers: `852` - Fetched arXiv records: `3203` - Unique arXiv records: `3089` - Filtered (non-target): `0` - Filtered (track): `0` - Filtered (no code links): `2237` | Category | Count | Gap to 1000 | |---|---:|---:| | Segmentation | 375 | 625 | | Reconstruction | 124 | 876 | | Classification | 327 | 673 | | Image Registration | 109 | 891 | | Domain Adaptation | 65 | 935 | | Generative Models | 183 | 817 | | General | 100 | 900 | ## 📊 Segmentation *This list is automatically generated. See any issues? Please open a pull request!* * **[Set-Inclusive Uncertainty Modeling for Robust Brain Tumor Segmentation](https://arxiv.org/abs/2606.30374v1)** - [Code](https://github.com/atlas-sky/sium) (confidence: high) * **[Mask to Concept: Auto-Promptable SAM3 via Efficient Test-Time Concept Embedding Search for Few-Shot Annotation](https://arxiv.org/abs/2606.26711v1)** - [Code](https://github.com/huster-hq/m2c) (confidence: high) * **[Interpretable Probabilistic Medical Image Segmentation via Gaussian Process with Explicit Modelling of Annotation Bias and Variability](https://arxiv.org/abs/2606.23177v1)** - [Code](https://github.com/qili111/gps-var) (confidence: high) * **[Surgical Anatomy Recognition with Context Learning using Foundation Representations](https://arxiv.org/abs/2606.22124v1)** - [Code](https://github.com/timjaspers0801/atlas) (confidence: medium) * **[Rethinking the Adaptation of Vision Foundation Models for Efficient Cell Segmentation](https://arxiv.org/abs/2606.21913v1)** - [Code](https://github.com/xq141839/efficell-seg) (confidence: high) * **[Single-Stage Hierarchical Rectification for Weakly Supervised Histopathology Segmentation](https://arxiv.org/abs/2606.20250v1)** - [Code](https://github.com/trongduc-nguyen/sshr) (confidence: high) * **[CSWinUNETR: Segmentation of Thin Anatomical Structures in Medical Images](https://arxiv.org/abs/2606.19824v1)** - [Code](https://github.com/labhai/cswinunetr) (confidence: high) * **[Quantification of Uncertainty with Adversarial Models in Medical Image Segmentation](https://arxiv.org/abs/2606.18860v1)** - [Code](https://github.com/hanajebril/quam_sm) (confidence: high) * **[Beyond Visual Cues: CoT-Enhanced Reasoning for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2606.17958v1)** - [Code](https://github.com/cymasuna/cers) (confidence: high) * **[Mutual Distillation of Dual-Foundation Models for Semi-Supervised PET/CT Segmentation](https://arxiv.org/abs/2606.15611v1)** - [Code](https://github.com/wu-beining/muduo) (confidence: high) * **[Attenuation-Resilient Alternating Optimization for Laparoscopic Liver Landmark Detection](https://arxiv.org/abs/2605.26630v1)** - [Code](https://github.com/hyperiondk115/a2onet) (confidence: medium) * **[Detail Consistent Stage-Wise Distillation for Efficient 3D MRI Segmentation](https://arxiv.org/abs/2605.26382v1)** - [Code](https://github.com/clinicaalpha/dcd-3d-medseg) (confidence: high) * **[Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation](https://arxiv.org/abs/2605.25402v3)** - [Code](https://github.com/zhcz328/anaus) (confidence: medium) * **[ImPartial: Multi-channel Whole-Cell Segmentation using Partial Annotations](https://arxiv.org/abs/2605.24128v1)** - [Code](https://github.com/nadeemlab/impartial) (confidence: high) * **[Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking](https://arxiv.org/abs/2605.23118v1)** - [Code](https://github.com/mic-dkfz/longiseg) (confidence: medium) * **[R2AoP: Reliable and Robust Angle of Progression Estimation from Intrapartum Ultrasound](https://arxiv.org/abs/2605.21099v1)** - [Code](https://github.com/baiyou1234/r2aop) (confidence: high) * **[Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings](https://arxiv.org/abs/2605.19374v1)** - [Code](https://github.com/dopaminelcy/conns) (confidence: medium) * **[VoxShield: Protecting 3D Medical Datasets from Unauthorized Training via Frequency-Aware Inter-Slice Disruption](https://arxiv.org/abs/2605.17345v1)** - [Code](https://github.com/kk266299/voxshield) (confidence: medium) * **[TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT](https://arxiv.org/abs/2605.16572v1)** - [Code](https://github.com/xmed-lab/trials) (confidence: high) * **[ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy](https://arxiv.org/abs/2605.11555v2)** - [Code](https://github.com/icherishxixixi/scribbledose) (confidence: medium) * **[XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity](https://arxiv.org/abs/2605.09639v2)** - [Code](https://github.com/alvinkimbowa/nntinyunet) (confidence: medium) * **[Defining Robust Ultrasound Quality Metrics via an Ultrasound Foundation Model](https://arxiv.org/abs/2604.19512v2)** - [Code](https://github.com/sextant-fable/us-metrics) (confidence: medium) * **[DUCX: Decomposing Unfairness in Tool-Using Chest X-ray Agents](https://arxiv.org/abs/2603.00777v2)** - [Code](https://github.com/nanboy-ronan/duck) (confidence: medium) * **[Glance and Focus Reinforcement for Pan-cancer Screening](https://arxiv.org/abs/2601.19103v2)** - [Code](https://github.com/luffy03/gf-screen) (confidence: high) * **[SSL-MedSAM2: A Semi-supervised Medical Image Segmentation Framework Powered by Few-shot Learning of SAM2](https://arxiv.org/abs/2512.11548v1)** - [Code](https://github.com/naisops/ssl-medsam2) (confidence: high) * **[The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning](https://arxiv.org/abs/2512.06206v1)** - [Code](https://github.com/fets-ai/challenge) (confidence: high) * **[MICCAI STSR 2025 Challenge: Semi-Supervised Teeth and Pulp Segmentation and CBCT-IOS Registration](https://arxiv.org/abs/2512.02867v1)** - [Code](https://github.com/ricoleehduu/sts-challenge-2025) (confidence: high) * **[MICCAI STS 2024 Challenge: Semi-Supervised Instance-Level Tooth Segmentation in Panoramic X-ray and CBCT Images](https://arxiv.org/abs/2511.22911v1)** - [Code](https://github.com/ricoleehduu/sts-challenge-2024) (confidence: high) * **[Hierarchical Semantic Learning for Multi-Class Aorta Segmentation](https://arxiv.org/abs/2511.14187v1)** - [Code](https://github.com/pengchengshi1220/aortaseg24) (confidence: high) | [Code2](https://github.com/pengchengshi1220/fractal-softmax) * **[MeisenMeister: A Simple Two Stage Pipeline for Breast Cancer Classification on MRI](https://arxiv.org/abs/2510.27326v1)** - [Code](https://github.com/mic-dkfz/meisenmeister) (confidence: medium) * **[SYNAPSE-Net: A Unified Framework with Lesion-Aware Hierarchical Gating for Robust Segmentation of Heterogeneous Brain Lesions](https://arxiv.org/abs/2510.26961v2)** - [Code](https://github.com/mubid-01/synapse-net-pre) (confidence: high) * **[How We Won BraTS-SSA 2025: Brain Tumor Segmentation in the Sub-Saharan African Population Using Segmentation-Aware Data Augmentation and Model Ensembling](https://arxiv.org/abs/2510.03568v2)** - [Code](https://github.com/spark-academy-2025/spark-2025) (confidence: high) * **[Domain-Specialized Interactive Segmentation Framework for Meningioma Radiotherapy Planning](https://arxiv.org/abs/2510.00416v1)** - [Code](https://github.com/snuh-rad-aicon/interactive-men-rt) (confidence: high) * **[U-Mamba2-SSL for Semi-Supervised Tooth and Pulp Segmentation in CBCT](https://arxiv.org/abs/2509.20154v2)** - [Code](https://github.com/zhiqin1998/umamba2) (confidence: high) * **[Anomaly Detection by Clustering DINO Embeddings using a Dirichlet Process Mixture](https://arxiv.org/abs/2509.19997v1)** - [Code](https://github.com/nicoschulthess/anomalydino-dpmm) (confidence: high) * **[Zero-shot Monocular Metric Depth for Endoscopic Images](https://arxiv.org/abs/2509.18642v1)** - [Code](https://github.com/touchsurgery/endosynth) (confidence: medium) * **[The Missing Piece: A Case for Pre-Training in 3D Medical Object Detection](https://arxiv.org/abs/2509.15947v1)** - [Code](https://github.com/mic-dkfz/nndetection-finetuning) (confidence: medium) * **[Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation](https://arxiv.org/abs/2509.13846v1)** - [Code](https://github.com/tenbatsu24/latentcampus) (confidence: high) * **[U-Mamba2: Scaling State Space Models for Dental Anatomy Segmentation in CBCT](https://arxiv.org/abs/2509.12069v3)** - [Code](https://github.com/zhiqin1998/umamba2) (confidence: high) * **[Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training](https://arxiv.org/abs/2509.09290v1)** - [Code](https://github.com/anthony-p-addison/agn-mod-seg) (confidence: high) * **[SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training](https://arxiv.org/abs/2509.08311v1)** - [Code](https://github.com/tonichopp/simcrop) (confidence: medium) * **[XOCT: Enhancing OCT to OCTA Translation via Cross-Dimensional Supervised Multi-Scale Feature Learning](https://arxiv.org/abs/2509.07455v1)** - [Code](https://github.com/uci-cbcl/xoct) (confidence: high) * **[Co-Seg: Mutual Prompt-Guided Collaborative Learning for Tissue and Nuclei Segmentation](https://arxiv.org/abs/2509.06740v1)** - [Code](https://github.com/xq141839/co-seg) (confidence: high) * **[Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation](https://arxiv.org/abs/2508.20909v2)** - [Code](https://github.com/yifangao112/dinounet) (confidence: high) * **[E-BayesSAM: Efficient Bayesian Adaptation of SAM with Self-Optimizing KAN-Based Interpretation for Uncertainty-Aware Ultrasonic Segmentation](https://arxiv.org/abs/2508.17408v1)** - [Code](https://github.com/mp31192/e-bayessam) (confidence: high) * **[Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing](https://arxiv.org/abs/2508.17326v1)** - [Code](https://github.com/tristan-deep/semantic-diffusion-echo-dehazing) (confidence: medium) * **[Comparing Conditional Diffusion Models for Synthesizing Contrast-Enhanced Breast MRI from Pre-Contrast Images](https://arxiv.org/abs/2508.13776v2)** - [Code](https://github.com/sebastibar/conditional-diffusion-breast-mri) (confidence: high) * **[What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?](https://arxiv.org/abs/2508.09381v1)** - [Code](https://github.com/sfu-mial/skin-iav) (confidence: high) * **[Conditional Fetal Brain Atlas Learning for Automatic Tissue Segmentation](https://arxiv.org/abs/2508.04522v1)** - [Code](https://github.com/cirmuw/fetal-brain-atlas) (confidence: high) * **[MAUP: Training-free Multi-center Adaptive Uncertainty-aware Prompting for Cross-domain Few-shot Medical Image Segmentation](https://arxiv.org/abs/2508.03511v1)** - [Code](https://github.com/yazhouzhu19/maup) (confidence: high) * **[GL-LCM: Global-Local Latent Consistency Models for Fast High-Resolution Bone Suppression in Chest X-Ray Images](https://arxiv.org/abs/2508.03357v1)** - [Code](https://github.com/diaoquesang/gl-lcm) (confidence: medium) * **[REFLECT: Rectified Flows for Efficient Brain Anomaly Correction Transport](https://arxiv.org/abs/2508.02889v1)** - [Code](https://github.com/farzad-bz/reflect) (confidence: medium) * **[M$^3$HL: Mutual Mask Mix with High-Low Level Feature Consistency for Semi-Supervised Medical Image Segmentation](https://arxiv.org/abs/2508.03752v1)** - [Code](https://github.com/phpjava666/m3hl) (confidence: high) * **[Large Kernel MedNeXt for Breast Tumor Segmentation and Self-Normalizing Network for pCR Classification in Magnetic Resonance Images](https://arxiv.org/abs/2508.01831v1)** - [Code](https://github.com/toufiqmusah/caladan-mama-mia) (confidence: high) * **[Skip priors and add graph-based anatomical information, for point-based Couinaud segmentation](https://arxiv.org/abs/2508.01785v1)** - [Code](https://github.com/zhangxiaotong015/grpn) (confidence: high) * **[GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation](https://arxiv.org/abs/2508.00155v1)** - [Code](https://github.com/tomek1911/gepar3d) (confidence: high) * **[Advancing Fetal Ultrasound Image Quality Assessment in Low-Resource Settings](https://arxiv.org/abs/2507.22802v1)** - [Code](https://github.com/donglihe-hub/fetalclip-iqa) (confidence: medium) * **[HRVVS: A High-resolution Video Vasculature Segmentation Network via Hierarchical Autoregressive Residual Priors](https://arxiv.org/abs/2507.22530v2)** - [Code](https://github.com/scott-yjyang/hrvvs) (confidence: high) * **[GLCP: Global-to-Local Connectivity Preservation for Tubular Structure Segmentation](https://arxiv.org/abs/2507.21328v1)** - [Code](https://github.com/feixiangzhou/glcp) (confidence: high) * **[EndoGen: Conditional Autoregressive Endoscopic Video Generation](https://arxiv.org/abs/2507.17388v1)** - [Code](https://github.com/cuhk-aim-group/endogen) (confidence: high) * **[Regularized Low-Rank Adaptation for Few-Shot Organ Segmentation](https://arxiv.org/abs/2507.15793v1)** - [Code](https://github.com/ghassenbaklouti/arena) (confidence: high) * **[Text-driven Multiplanar Visual Interaction for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2507.12382v1)** - [Code](https://github.com/taozh2017/text-semiseg) (confidence: high) * **[A Composite Alignment-Aware Framework for Myocardial Lesion Segmentation in Multi-sequence CMR Images](https://arxiv.org/abs/2507.11886v1)** - [Code](https://github.com/yifangao112/caa-seg) (confidence: high) * **[RadiomicsRetrieval: A Customizable Framework for Medical Image Retrieval Using Radiomics Features](https://arxiv.org/abs/2507.08546v1)** - [Code](https://github.com/nainye/radiomicsretrieval) (confidence: medium) * **[Cycle Context Verification for In-Context Medical Image Segmentation](https://arxiv.org/abs/2507.08357v1)** - [Code](https://github.com/shishuaihu/ccv) (confidence: high) * **[Learning Segmentation from Radiology Reports](https://arxiv.org/abs/2507.05582v1)** - [Code](https://github.com/mrgiovanni/r-super) (confidence: high) * **[T-SYNTH: A Knowledge-Based Dataset of Synthetic Breast Images](https://arxiv.org/abs/2507.04038v2)** - [Code](https://github.com/didsr/tsynth-release) (confidence: medium) * **[Learning Disentangled Stain and Structural Representations for Semi-Supervised Histopathology Segmentation](https://arxiv.org/abs/2507.03923v2)** - [Code](https://github.com/hieuphamha19/csds) (confidence: high) * **[SAMed-2: Selective Memory Enhanced Medical Segment Anything Model](https://arxiv.org/abs/2507.03698v1)** - [Code](https://github.com/zhilingyan/medical-sam-bench) (confidence: high) * **[Structure and Smoothness Constrained Dual Networks for MR Bias Field Correction](https://arxiv.org/abs/2507.01326v1)** - [Code](https://github.com/leongdong/s2dnets) (confidence: medium) * **[Text-Guided Multi-Instance Learning for Scoliosis Screening via Gait Video Analysis](https://arxiv.org/abs/2507.02996v1)** - [Code](https://github.com/lhqqq/tg-milnet) (confidence: medium) * **[TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency](https://arxiv.org/abs/2507.00802v2)** - [Code](https://github.com/vinyehshaw/trace) (confidence: medium) * **[MTCNet: Motion and Topology Consistency Guided Learning for Mitral Valve Segmentationin 4D Ultrasound](https://arxiv.org/abs/2507.00660v2)** - [Code](https://github.com/crs524/mtcnet) (confidence: medium) * **[MadCLIP: Few-shot Medical Anomaly Detection with CLIP](https://arxiv.org/abs/2506.23810v1)** - [Code](https://github.com/mahshid1998/madclip) (confidence: medium) * **[Single Image Test-Time Adaptation via Multi-View Co-Training](https://arxiv.org/abs/2506.23705v1)** - [Code](https://github.com/smriti-joshi/muvi) (confidence: medium) * **[SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting](https://arxiv.org/abs/2506.23309v2)** - [Code](https://github.com/lastbasket/surgtpgs) (confidence: high) * **[FedCLAM: Client Adaptive Momentum with Foreground Intensity Matching for Federated Medical Image Segmentation](https://arxiv.org/abs/2506.22580v1)** - [Code](https://github.com/siomvas/fedclam) (confidence: high) * **[Cardiovascular disease classification using radiomics and geometric features from cardiac CT](https://arxiv.org/abs/2506.22226v2)** - [Code](https://github.com/biomedia-mira/grc-net) (confidence: medium) * **[Tied Prototype Model for Few-Shot Medical Image Segmentation](https://arxiv.org/abs/2506.22101v1)** - [Code](https://github.com/hjk92g/tpm-fss) (confidence: high) * **[Exploring the Design Space of 3D MLLMs for CT Report Generation](https://arxiv.org/abs/2506.21535v2)** - [Code](https://github.com/bowang-lab/amos-mm-solution) (confidence: high) * **[HyperSORT: Self-Organising Robust Training with hyper-networks](https://arxiv.org/abs/2506.21430v1)** - [Code](https://github.com/imfusiongmbh/hypersort) (confidence: high) * **[AdvMIM: Adversarial Masked Image Modeling for Semi-Supervised Medical Image Segmentation](https://arxiv.org/abs/2506.20563v1)** - [Code](https://github.com/zlheui/advmim) (confidence: high) * **[VoxelOpt: Voxel-Adaptive Message Passing for Discrete Optimization in Deformable Abdominal CT Registration](https://arxiv.org/abs/2506.19975v1)** - [Code](https://github.com/tinymilky/voxelopt) (confidence: medium) * **[SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus](https://arxiv.org/abs/2506.18404v1)** - [Code](https://github.com/yifangao112/safeclick) (confidence: high) * **[Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster](https://arxiv.org/abs/2506.18034v1)** - [Code](https://github.com/fenghetan9/llm4seg) (confidence: high) * **[LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images](https://arxiv.org/abs/2506.17983v2)** - [Code](https://github.com/scy-jackel/lvpnet) (confidence: medium) * **[Mono-Modalizing Extremely Heterogeneous Multi-Modal Medical Image Registration](https://arxiv.org/abs/2506.15596v2)** - [Code](https://github.com/micv-yonsei/m2m-reg) (confidence: medium) * **[DSSAU-Net:U-Shaped Hybrid Network for Pubic Symphysis and Fetal Head Segmentation](https://arxiv.org/abs/2506.03684v1)** - [Code](https://github.com/xiazunhui/dssau-net) (confidence: high) * **[CENet: Context Enhancement Network for Medical Image Segmentation](https://arxiv.org/abs/2505.18423v1)** - [Code](https://github.com/xmindflow/cenet) (confidence: high) * **[Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing Modalities](https://arxiv.org/abs/2505.16809v3)** - [Code](https://github.com/reeive/rehydil) (confidence: high) * **[HWA-UNETR: Hierarchical Window Aggregate UNETR for 3D Multimodal Gastric Lesion Segmentation](https://arxiv.org/abs/2505.10464v3)** - [Code](https://github.com/jeming-creater/hwa-unetr) (confidence: high) * **[ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking](https://arxiv.org/abs/2505.08581v1)** - [Code](https://github.com/jinlab-imvr/resurgsam2) (confidence: high) * **[Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge](https://arxiv.org/abs/2503.24306v1)** - [Code](https://github.com/athaddius/stirmetrics) (confidence: medium) * **[Modality-Agnostic Brain Lesion Segmentation with Privacy-aware Continual Learning](https://arxiv.org/abs/2503.20326v2)** - [Code](https://github.com/xmindflow/braincl) (confidence: high) * **[CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention](https://arxiv.org/abs/2503.15949v1)** - [Code](https://github.com/wutcm-lab/causalclipseg) (confidence: high) * **[One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks](https://arxiv.org/abs/2503.14979v1)** - [Code](https://github.com/medaitech/tcmn) (confidence: high) * **[Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning](https://arxiv.org/abs/2503.14958v1)** - [Code](https://github.com/medaitech/rab) (confidence: high) * **[Striving for Simplicity: Simple Yet Effective Prior-Aware Pseudo-Labeling for Semi-Supervised Ultrasound Image Segmentation](https://arxiv.org/abs/2503.13987v1)** - [Code](https://github.com/wutcm-lab/shape-prior-semi-seg) (confidence: high) * **[CyclePose -- Leveraging Cycle-Consistency for Annotation-Free Nuclei Segmentation in Fluorescence Microscopy](https://arxiv.org/abs/2503.11266v2)** - [Code](https://github.com/jonasutz/cyclepose) (confidence: high) * **[Conditional diffusion model with spatial attention and latent embedding for medical image segmentation](https://arxiv.org/abs/2502.06997v2)** - [Code](https://github.com/hejrati/cdal) (confidence: high) * **[SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data](https://arxiv.org/abs/2412.16078v1)** - [Code](https://github.com/surgical-vision/segcol_challenge) (confidence: high) * **[Parameter-efficient Fine-tuning for improved Convolutional Baseline for Brain Tumor Segmentation in Sub-Saharan Africa Adult Glioma Dataset](https://arxiv.org/abs/2412.14100v1)** - [Code](https://github.com/camera-mri/spark2024) (confidence: high) * **[Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation](https://arxiv.org/abs/2412.04094v3)** - [Code](https://github.com/precision-medical-imaging-group/hope-segmenter-kids) (confidence: high) * **[SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation](https://arxiv.org/abs/2411.12602v1)** - [Code](https://github.com/multimodallearning/samcarriestheburden) (confidence: high) * **[HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation](https://arxiv.org/abs/2411.03976v2)** - [Code](https://github.com/cviu-csu/hrdecoder) (confidence: high) * **[EchoNarrator: Generating natural text explanations for ejection fraction predictions](https://arxiv.org/abs/2410.23744v1)** - [Code](https://github.com/guybenyosef/echonarrator) (confidence: medium) * **[A Bayesian Approach to Weakly-supervised Laparoscopic Image Segmentation](https://arxiv.org/abs/2410.08509v1)** - [Code](https://github.com/morilabnu/bayesian_wss) (confidence: high) * **[DB-SAM: Delving into High Quality Universal Medical Image Segmentation](https://arxiv.org/abs/2410.04172v1)** - [Code](https://github.com/alfredqin/db-sam) (confidence: high) * **[Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision](https://arxiv.org/abs/2409.20293v1)** - [Code](https://github.com/minimel/medsamweakfewshotpromptautomation) (confidence: high) * **[Self-supervised Pretraining for Cardiovascular Magnetic Resonance Cine Segmentation](https://arxiv.org/abs/2409.18100v1)** - [Code](https://github.com/q-cardia/ssp-cmr-cine-segmentation) (confidence: high) * **[SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2409.16728v2)** - [Code](https://github.com/pascalcpp/sdcl) (confidence: high) * **[Multiscale Encoder and Omni-Dimensional Dynamic Convolution Enrichment in nnU-Net for Brain Tumor Segmentation](https://arxiv.org/abs/2409.13229v1)** - [Code](https://github.com/i-sahajmistry/nnunet_brats2023) (confidence: high) * **[Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2409.12522v1)** - [Code](https://github.com/wkklavis/dapsam) (confidence: high) * **[Intrapartum Ultrasound Image Segmentation of Pubic Symphysis and Fetal Head Using Dual Student-Teacher Framework with CNN-ViT Collaborative Learning](https://arxiv.org/abs/2409.06928v1)** - [Code](https://github.com/jjm1589/dstct) (confidence: high) * **[Curriculum Prompting Foundation Models for Medical Image Segmentation](https://arxiv.org/abs/2409.00695v1)** - [Code](https://github.com/annazzz-zxq/curriculum-prompting) (confidence: high) * **[Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance](https://arxiv.org/abs/2408.15217v1)** - [Code](https://github.com/michi-3000/fundus2video) (confidence: high) * **[Enhancing Cross-Modal Medical Image Segmentation through Compositionality](https://arxiv.org/abs/2408.11733v1)** - [Code](https://github.com/trustworthy-ai-uu-nki/cross-modal-segmentation) (confidence: high) * **[FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentation](https://arxiv.org/abs/2408.11701v1)** - [Code](https://github.com/trustworthy-ai-uu-nki/federated-learning-disentanglement) (confidence: high) * **[RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction](https://arxiv.org/abs/2408.07325v1)** - [Code](https://github.com/chenhbo/rocosdf) (confidence: medium) * **[BMFT: Achieving Fairness via Bias-based Weight Masking Fine-tuning](https://arxiv.org/abs/2408.06890v2)** - [Code](https://github.com/vios-s/bmft) (confidence: medium) * **[S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation](https://arxiv.org/abs/2408.06447v1)** - [Code](https://github.com/jayparanjape/svdsam) (confidence: high) * **[HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training](https://arxiv.org/abs/2408.05815v1)** - [Code](https://github.com/fenghetan9/hyspark) (confidence: medium) * **[Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis](https://arxiv.org/abs/2408.03035v2)** - [Code](https://github.com/gungui98/echo-free) (confidence: medium) * **[Segmenting Small Stroke Lesions with Novel Labeling Strategies](https://arxiv.org/abs/2408.02929v1)** - [Code](https://github.com/nadluru/strokelesseg) (confidence: high) * **[Segmentation Style Discovery: Application to Skin Lesion Images](https://arxiv.org/abs/2408.02787v1)** - [Code](https://github.com/sfu-mial/styleseg) (confidence: high) * **[AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation](https://arxiv.org/abs/2408.00640v2)** - [Code](https://github.com/asbjrnmunk/amaes) (confidence: high) * **[Robust Conformal Volume Estimation in 3D Medical Images](https://arxiv.org/abs/2407.19938v1)** - [Code](https://github.com/benolmbrt/wcp_miccai) (confidence: medium) * **[Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation](https://arxiv.org/abs/2407.19284v2)** - [Code](https://github.com/lkpengcs/syntumoranalyzer) (confidence: high) * **[Mask-Free Neuron Concept Annotation for Interpreting Neural Networks in Medical Domain](https://arxiv.org/abs/2407.11375v1)** - [Code](https://github.com/ailab-kyunghee/mammi) (confidence: medium) * **[DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2407.09918v1)** - [Code](https://github.com/cuhk-aim-group/diffrect) (confidence: high) * **[Let Me DeCode You: Decoder Conditioning with Tabular Data](https://arxiv.org/abs/2407.09437v1)** - [Code](https://github.com/sanoscience/decode) (confidence: medium) * **[Region Attention Transformer for Medical Image Restoration](https://arxiv.org/abs/2407.09268v1)** - [Code](https://github.com/yaziwel/region-attention-transformer-for-medical-image-restoration) (confidence: medium) * **[Symmetry Awareness Encoded Deep Learning Framework for Brain Imaging Analysis](https://arxiv.org/abs/2407.08948v1)** - [Code](https://github.com/bitmyron/sa-swin) (confidence: medium) * **[Progressive Growing of Patch Size: Resource-Efficient Curriculum Learning for Dense Prediction Tasks](https://arxiv.org/abs/2407.07853v2)** - [Code](https://github.com/compai-lab/2024-miccai-fischer) (confidence: medium) * **[Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation](https://arxiv.org/abs/2407.07514v1)** - [Code](https://github.com/mi2datalab/swinsmt) (confidence: high) * **[Weakly-supervised Medical Image Segmentation with Gaze Annotations](https://arxiv.org/abs/2407.07406v1)** - [Code](https://github.com/med-air/gazemedseg) (confidence: high) * **[FairDiff: Fair Segmentation with Point-Image Diffusion](https://arxiv.org/abs/2407.06250v1)** - [Code](https://github.com/wenyi-li/fairdiff) (confidence: high) * **[Training-free CryoET Tomogram Segmentation](https://arxiv.org/abs/2407.06833v1)** - [Code](https://github.com/xulabs/aitom) (confidence: high) * **[Self-Paced Sample Selection for Barely-Supervised Medical Image Segmentation](https://arxiv.org/abs/2407.05248v1)** - [Code](https://github.com/suuujm/spss) (confidence: high) * **[Embracing Massive Medical Data](https://arxiv.org/abs/2407.04687v1)** - [Code](https://github.com/mrgiovanni/onlinelearning) (confidence: medium) * **[HyperSpace: Hypernetworks for spacing-adaptive image segmentation](https://arxiv.org/abs/2407.03681v1)** - [Code](https://github.com/imfusiongmbh/hyperspace) (confidence: high) * **[An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation](https://arxiv.org/abs/2407.02893v2)** - [Code](https://github.com/hilab-git/ugtst) (confidence: high) * **[FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness](https://arxiv.org/abs/2407.02280v2)** - [Code](https://github.com/hustxyy/fedia) (confidence: high) * **[Centerline Boundary Dice Loss for Vascular Segmentation](https://arxiv.org/abs/2407.01517v1)** - [Code](https://github.com/pengchengshi1220/cbdice) (confidence: high) * **[SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues](https://arxiv.org/abs/2406.19364v3)** - [Code](https://github.com/xyx1024/simtxtseg) (confidence: high) * **[BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision](https://arxiv.org/abs/2406.19148v1)** - [Code](https://github.com/kitbransby/backmix) (confidence: medium) * **[Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis](https://arxiv.org/abs/2406.18967v2)** - [Code](https://github.com/hieuphan33/miccai2024-unest) (confidence: medium) * **[Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process](https://arxiv.org/abs/2406.18361v3)** - [Code](https://github.com/lin-tianyu/stable-diffusion-seg) (confidence: high) * **[Scalp Diagnostic System With Label-Free Segmentation and Training-Free Image Translation](https://arxiv.org/abs/2406.17254v3)** - [Code](https://github.com/winston1214/scalpvision) (confidence: high) * **[SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation](https://arxiv.org/abs/2406.14896v1)** - [Code](https://github.com/chongqingnosubway/selfreg-unet) (confidence: high) * **[Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases](https://arxiv.org/abs/2406.13674v1)** - [Code](https://github.com/luoxd1996/raos) (confidence: high) * **[Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center Dataset](https://arxiv.org/abs/2406.13645v1)** - [Code](https://github.com/whq-xxh/sfada-uwf-slo) (confidence: high) * **[SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation](https://arxiv.org/abs/2406.13532v1)** - [Code](https://github.com/scatteredrain/sali) (confidence: high) * **[LNQ Challenge 2023: Learning Mediastinal Lymph Node Segmentation with a Probabilistic Lymph Node Atlas](https://arxiv.org/abs/2406.03984v1)** - [Code](https://github.com/micai-imi-uzl/lnq2023) (confidence: high) * **[SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression](https://arxiv.org/abs/2405.16813v4)** - [Code](https://github.com/oulu-imeds/singr) (confidence: high) * **[Memory-efficient High-resolution OCT Volume Synthesis with Cascaded Amortized Latent Diffusion Models](https://arxiv.org/abs/2405.16516v1)** - [Code](https://github.com/nicetomeetu21/ca-ldm) (confidence: medium) * **[Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation](https://arxiv.org/abs/2405.16102v1)** - [Code](https://github.com/zenghy96/reliable-source-approximation) (confidence: high) * **[Patient-Specific Real-Time Segmentation in Trackerless Brain Ultrasound](https://arxiv.org/abs/2405.09959v1)** - [Code](https://github.com/reubendo/mhvae-seg) (confidence: high) * **[M$^4$oE: A Foundation Model for Medical Multimodal Image Segmentation with Mixture of Experts](https://arxiv.org/abs/2405.09446v1)** - [Code](https://github.com/jefferyjiang-yf/m4oe) (confidence: high) * **[VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks](https://arxiv.org/abs/2405.06196v2)** - [Code](https://github.com/naamiinepal/vlsm-adapter) (confidence: high) * **[LHU-Net: a Lean Hybrid U-Net for Cost-efficient, High-performance Volumetric Segmentation](https://arxiv.org/abs/2404.05102v3)** - [Code](https://github.com/xmindflow/lhunet) (confidence: high) * **[Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks](https://arxiv.org/abs/2403.19880v1)** - [Code](https://github.com/pooria90/diffecho) (confidence: medium) * **[Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation](https://arxiv.org/abs/2403.09942v1)** - [Code](https://github.com/yaziciz/glims) (confidence: high) * **[LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation](https://arxiv.org/abs/2403.07332v2)** - [Code](https://github.com/wjh892521292/lkm-unet) (confidence: high) * **[Shortcut Learning in Medical Image Segmentation](https://arxiv.org/abs/2403.06748v2)** - [Code](https://github.com/nina-weng/shortcut_skinseg) (confidence: high) * **[FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation](https://arxiv.org/abs/2403.05408v2)** - [Code](https://github.com/liu-yuxi/fedfms) (confidence: high) * **[MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation](https://arxiv.org/abs/2402.17725v2)** - [Code](https://github.com/hananshafi/medcontext) (confidence: high) * **[Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models](https://arxiv.org/abs/2402.05210v4)** - [Code](https://github.com/mazurowski-lab/segmentation-guided-diffusion) (confidence: high) * **[VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification](https://arxiv.org/abs/2402.01034v3)** - [Code](https://github.com/lzl199704/vis-mae) (confidence: high) * **[MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head](https://arxiv.org/abs/2401.15513v1)** - [Code](https://github.com/13204942/mitu-net) (confidence: medium) * **[Pixel-Wise Recognition for Holistic Surgical Scene Understanding](https://arxiv.org/abs/2401.11174v2)** - [Code](https://github.com/bcv-uniandes/grasp) (confidence: medium) * **[TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer](https://arxiv.org/abs/2311.13234v1)** - [Code](https://github.com/huiminxiong/tsegformer) (confidence: high) * **[Diffusion-based Data Augmentation for Nuclei Image Segmentation](https://arxiv.org/abs/2310.14197v2)** - [Code](https://github.com/lhaof/nudiff) (confidence: high) * **[ASC: Appearance and Structure Consistency for Unsupervised Domain Adaptation in Fetal Brain MRI Segmentation](https://arxiv.org/abs/2310.14172v1)** - [Code](https://github.com/lhaof/asc) (confidence: high) * **[Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration](https://arxiv.org/abs/2310.11040v3)** - [Code](https://github.com/brain-intelligence-lab/girnet) (confidence: high) * **[Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation](https://arxiv.org/abs/2310.10493v1)** - [Code](https://github.com/hvcl/sam_interactive_histopathology) (confidence: high) * **[BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision](https://arxiv.org/abs/2310.07060v1)** - [Code](https://github.com/prantik-pdeb/best-les) (confidence: high) * **[Fully Automatic Segmentation of Gross Target Volume and Organs-at-Risk for Radiotherapy Planning of Nasopharyngeal Carcinoma](https://arxiv.org/abs/2310.02972v1)** - [Code](https://github.com/astarakee/segrap2023) (confidence: high) * **[RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches](https://arxiv.org/abs/2310.00868v2)** - [Code](https://github.com/nadeemlab/cep) (confidence: medium) * **[Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision](https://arxiv.org/abs/2309.15358v1)** - [Code](https://github.com/jlianglab/eden) (confidence: medium) * **[A mirror-Unet architecture for PET/CT lesion segmentation](https://arxiv.org/abs/2309.13398v1)** - [Code](https://github.com/yrotstein/autopet2023_mv1) (confidence: high) * **[AutoPET Challenge 2023: Sliding Window-based Optimization of U-Net](https://arxiv.org/abs/2309.12114v2)** - [Code](https://github.com/matt3o/autopet2-submission) (confidence: high) * **[GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation](https://arxiv.org/abs/2309.11144v1)** - [Code](https://github.com/xmed-lab/gl-fusion) (confidence: high) * **[Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting](https://arxiv.org/abs/2309.06824v2)** - [Code](https://github.com/xianlin7/samus) (confidence: high) * **[A Localization-to-Segmentation Framework for Automatic Tumor Segmentation in Whole-Body PET/CT Images](https://arxiv.org/abs/2309.05446v2)** - [Code](https://github.com/medcai/l2snet) (confidence: high) * **[Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer](https://arxiv.org/abs/2309.04825v1)** - [Code](https://github.com/yazhouzhu19/rpt) (confidence: high) * **[ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation](https://arxiv.org/abs/2309.05674v1)** - [Code](https://github.com/xianlin7/convformer) (confidence: high) * **[Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning](https://arxiv.org/abs/2309.03440v1)** - [Code](https://github.com/ladderlab-xjtu/deeppwml) (confidence: high) * **[DARC: Distribution-Aware Re-Coloring Model for Generalizable Nucleus Segmentation](https://arxiv.org/abs/2309.00188v1)** - [Code](https://github.com/csccsccsccsc/darc) (confidence: high) * **[Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection](https://arxiv.org/abs/2309.00108v1)** - [Code](https://github.com/mindflow-institue/laplacian-former) (confidence: medium) * **[CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention](https://arxiv.org/abs/2308.16145v2)** - [Code](https://github.com/zhanghx-iim-ahu/circleformer) (confidence: medium) * **[Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data](https://arxiv.org/abs/2308.15881v1)** - [Code](https://github.com/nki-radiology/interpretability_augmentation) (confidence: high) * **[Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers](https://arxiv.org/abs/2308.13442v2)** - [Code](https://github.com/mindflow-institue/waveformer) (confidence: high) * **[Test-time augmentation-based active learning and self-training for label-efficient segmentation](https://arxiv.org/abs/2308.10727v1)** - [Code](https://github.com/bella31/tta-quality-estimation-st-al) (confidence: high) * **[Inferior Alveolar Nerve Segmentation in CBCT images using Connectivity-Based Selective Re-training](https://arxiv.org/abs/2308.09298v1)** - [Code](https://github.com/garynico517/ssl-ian-retraining) (confidence: high) * **[LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation](https://arxiv.org/abs/2308.09026v1)** - [Code](https://github.com/dogabasaran/lesionmix) (confidence: high) * **[Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation](https://arxiv.org/abs/2308.07731v1)** - [Code](https://github.com/xmed-lab/cpr) (confidence: high) * **[DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation](https://arxiv.org/abs/2308.02959v1)** - [Code](https://github.com/mindflow-institue/dermosegdiff) (confidence: high) * **[Boundary Difference Over Union Loss For Medical Image Segmentation](https://arxiv.org/abs/2308.00220v1)** - [Code](https://github.com/sunfan-bvb/boundarydouloss) (confidence: high) * **[Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation](https://arxiv.org/abs/2307.16143v2)** - [Code](https://github.com/hieuphan33/maskgan) (confidence: high) * **[Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation](https://arxiv.org/abs/2307.15645v1)** - [Code](https://github.com/splinterli/sattca) (confidence: high) * **[vox2vec: A Framework for Self-supervised Contrastive Learning of Voxel-level Representations in Medical Images](https://arxiv.org/abs/2307.14725v1)** - [Code](https://github.com/mishgon/vox2vec) (confidence: medium) * **[Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free Approach](https://arxiv.org/abs/2307.14446v1)** - [Code](https://github.com/mindflow-institue/annotation_free_fewshot) (confidence: high) * **[AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets](https://arxiv.org/abs/2307.13897v2)** - [Code](https://github.com/siyi-wind/avit) (confidence: high) * **[SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation](https://arxiv.org/abs/2307.12591v1)** - [Code](https://github.com/ucsc-vlaa/swinmm) (confidence: high) * **[Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging](https://arxiv.org/abs/2307.12542v2)** - [Code](https://github.com/med-air/client-dp-fl) (confidence: medium) * **[SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings](https://arxiv.org/abs/2307.12429v2)** - [Code](https://github.com/charzharr/miccai23-swipe-implicit-segmentation) (confidence: high) * **[COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation](https://arxiv.org/abs/2307.12004v1)** - [Code](https://github.com/medicl-vu/colossal) (confidence: high) * **[Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation](https://arxiv.org/abs/2307.11604v1)** - [Code](https://github.com/aijinrjinr/mlb-seg) (confidence: high) * **[Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios](https://arxiv.org/abs/2307.10955v1)** - [Code](https://github.com/zzzzzzpc/funet) (confidence: high) * **[WeakPolyp: You Only Look Bounding Box for Polyp Segmentation](https://arxiv.org/abs/2307.10912v1)** - [Code](https://github.com/weijun88/weakpolyp) (confidence: high) * **[EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation](https://arxiv.org/abs/2307.08473v1)** - [Code](https://github.com/jcruan519/ege-unet) (confidence: high) * **[Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network](https://arxiv.org/abs/2307.08268v2)** - [Code](https://github.com/alibaba-damo-academy/pixel-lesion-patient-network) (confidence: high) * **[Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation](https://arxiv.org/abs/2307.07269v2)** - [Code](https://github.com/asif-hanif/vafa) (confidence: high) * **[Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training](https://arxiv.org/abs/2307.07246v2)** - [Code](https://github.com/chenxiaofei-cs/kobo) (confidence: medium) * **[Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation](https://arxiv.org/abs/2307.05898v1)** - [Code](https://github.com/beileicui/ms-tfal) (confidence: high) * **[CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation](https://arxiv.org/abs/2307.04513v2)** - [Code](https://github.com/ycwu1997/coactseg) (confidence: high) * **[Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery](https://arxiv.org/abs/2307.03662v1)** - [Code](https://github.com/br0202/sensing_area_detection) (confidence: medium) * **[Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation](https://arxiv.org/abs/2307.03008v3)** - [Code](https://github.com/j-morano/multimodal-ssl-fpn) (confidence: high) * **[Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning](https://arxiv.org/abs/2307.02798v1)** - [Code](https://github.com/hritam-98/gfda-disentangled) (confidence: high) * **[LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion](https://arxiv.org/abs/2307.02452v2)** - [Code](https://github.com/longbai1006/llcaps) (confidence: medium) * **[MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets](https://arxiv.org/abs/2307.02100v3)** - [Code](https://github.com/siyi-wind/mdvit) (confidence: high) * **[H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation](https://arxiv.org/abs/2307.01486v1)** - [Code](https://github.com/shijun18/h-denseformer) (confidence: high) * **[Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train](https://arxiv.org/abs/2306.16741v4)** - [Code](https://github.com/med-air/endo-fm) (confidence: medium) * **[Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset](https://arxiv.org/abs/2306.07089v2)** - [Code](https://github.com/m3dv/pulmonary-tree-repairing) (confidence: medium) * **[ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer](https://arxiv.org/abs/2306.05688v1)** - [Code](https://github.com/zax130/smilecode) (confidence: medium) * **[Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation](https://arxiv.org/abs/2306.05254v2)** - [Code](https://github.com/shishuaihu/ccsdg) (confidence: high) * **[Instructive Feature Enhancement for Dichotomous Medical Image Segmentation](https://arxiv.org/abs/2306.03497v1)** - [Code](https://github.com/yezi-66/ife) (confidence: high) * **[DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2306.00499v2)** - [Code](https://github.com/yifangao112/desam) (confidence: high) * **[S$^2$ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-supervised Polyp Segmentation](https://arxiv.org/abs/2306.00451v1)** - [Code](https://github.com/lofrienger/s2me) (confidence: high) * **[Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentation](https://arxiv.org/abs/2305.19949v1)** - [Code](https://github.com/chen-ziyang/trid) (confidence: high) * **[DENTEX: Dental Enumeration and Tooth Pathosis Detection Benchmark for Panoramic X-ray](https://arxiv.org/abs/2305.19112v2)** - [Code](https://github.com/ibrahimethemhamamci/dentex) (confidence: medium) * **[Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions](https://arxiv.org/abs/2305.18830v1)** - [Code](https://github.com/hilab-git/cdma) (confidence: high) * **[3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge](https://arxiv.org/abs/2305.18277v1)** - [Code](https://github.com/abenhamadou/3dteethseg22_challenge) (confidence: high) * **[FUSegNet: A Deep Convolutional Neural Network for Foot Ulcer Segmentation](https://arxiv.org/abs/2305.02961v2)** - [Code](https://github.com/mrinal054/fusegnet) (confidence: high) * **[DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models](https://arxiv.org/abs/2304.13416v2)** - [Code](https://github.com/shaoshitong/diffuseexpand) (confidence: high) * **[SurgicalGPT: End-to-End Language-Vision GPT for Visual Question Answering in Surgery](https://arxiv.org/abs/2304.09974v2)** - [Code](https://github.com/lalithjets/surgicalgpt) (confidence: medium) * **[Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels](https://arxiv.org/abs/2303.16296v4)** - [Code](https://github.com/zifuwanggg/jdtlosses) (confidence: medium) * **[Few Shot Medical Image Segmentation with Cross Attention Transformer](https://arxiv.org/abs/2303.13867v3)** - [Code](https://github.com/hust-linyi/cat-net) (confidence: high) * **[MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation](https://arxiv.org/abs/2303.09975v5)** - [Code](https://github.com/mic-dkfz/mednext) (confidence: high) * **[Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation](https://arxiv.org/abs/2303.06040v3)** - [Code](https://github.com/mathpluscode/imgx-diffseg) (confidence: high) * **[Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation](https://arxiv.org/abs/2303.05785v2)** - [Code](https://github.com/masilab/repux-net) (confidence: high) * **[TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation](https://arxiv.org/abs/2301.06624v1)** - [Code](https://github.com/melinphd/taal) (confidence: high) * **[DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation](https://arxiv.org/abs/2212.13504v3)** - [Code](https://github.com/mindflow-institue/daeformer) (confidence: high) * **[MAPPING: Model Average with Post-processing for Stroke Lesion Segmentation](https://arxiv.org/abs/2211.15486v1)** - [Code](https://github.com/king-haw/atlas-r2-docker-submission) (confidence: high) * **[CircleSnake: Instance Segmentation with Circle Representation](https://arxiv.org/abs/2211.01254v1)** - [Code](https://github.com/hrlblab/circlesnake) (confidence: high) * **[Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation](https://arxiv.org/abs/2210.08652v1)** - [Code](https://github.com/masilab/dcc_cl) (confidence: high) * **[Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans](https://arxiv.org/abs/2210.07490v1)** - [Code](https://github.com/yejin0111/autopet2022_blackbean) (confidence: high) * **[Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks](https://arxiv.org/abs/2209.15287v1)** - [Code](https://github.com/rakshith2597/quantised-self-attentive-deep-neural-network) (confidence: medium) * **[Open-source tool for Airway Segmentation in Computed Tomography using 2.5D Modified EfficientDet: Contribution to the ATM22 Challenge](https://arxiv.org/abs/2209.15094v2)** - [Code](https://github.com/miclab-unicamp/medseg) (confidence: high) * **[3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation](https://arxiv.org/abs/2209.15076v4)** - [Code](https://github.com/masilab/3dux-net) (confidence: high) * **[Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers](https://arxiv.org/abs/2209.11268v1)** - [Code](https://github.com/wangkaiwan/hecktor-2022-airt) (confidence: high) * **[Attentive Symmetric Autoencoder for Brain MRI Segmentation](https://arxiv.org/abs/2209.08887v1)** - [Code](https://github.com/lhaof/asa) (confidence: high) * **[Noise transfer for unsupervised domain adaptation of retinal OCT images](https://arxiv.org/abs/2209.08097v1)** - [Code](https://github.com/valentinkoch/svdna) (confidence: medium) * **[Automatic Tumor Segmentation via False Positive Reduction Network for Whole-Body Multi-Modal PET/CT Images](https://arxiv.org/abs/2209.07705v1)** - [Code](https://github.com/yigepeng/autopet_false_positive_reduction) (confidence: high) * **[HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation](https://arxiv.org/abs/2209.07313v1)** - [Code](https://github.com/kytimmylai/dfuc2022) (confidence: high) | [Code2](https://github.com/yuwenlo/hardnet-dfus) * **[Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://arxiv.org/abs/2209.06861v1)** - [Code](https://github.com/davecasp/flowssm) (confidence: medium) * **[On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness](https://arxiv.org/abs/2209.06078v2)** - [Code](https://github.com/agaldran/lesion_losses_ood) (confidence: high) * **[DOMINO: Domain-aware Model Calibration in Medical Image Segmentation](https://arxiv.org/abs/2209.06077v1)** - [Code](https://github.com/lab-smile/domino) (confidence: high) * **[Learning correspondences of cardiac motion from images using biomechanics-informed modeling](https://arxiv.org/abs/2209.00726v1)** - [Code](https://github.com/voldemort108x/bioinformed_reg) (confidence: medium) * **[SFusion: Self-attention based N-to-One Multimodal Fusion Block](https://arxiv.org/abs/2208.12776v2)** - [Code](https://github.com/scut-cszcl/sfusion) (confidence: medium) * **[PARSE challenge 2022: Pulmonary Arteries Segmentation using Swin U-Net Transformer(Swin UNETR) and U-Net](https://arxiv.org/abs/2208.09636v1)** - [Code](https://github.com/akansh12/parse2022) (confidence: high) * **[Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning](https://arxiv.org/abs/2208.08226v2)** - [Code](https://github.com/miccai2022-155/autoseg) (confidence: high) * **[Using Large Context for Kidney Multi-Structure Segmentation from CTA Images](https://arxiv.org/abs/2208.04525v3)** - [Code](https://github.com/fengjiejiejiejie/kipa22_nnunet) (confidence: high) * **[Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images](https://arxiv.org/abs/2208.03327v1)** - [Code](https://github.com/marwankefah/sissi) (confidence: medium) * **[Automatic Segmentation of the Placenta in BOLD MRI Time Series](https://arxiv.org/abs/2208.02895v1)** - [Code](https://github.com/mabulnaga/automatic-placenta-segmentation) (confidence: high) * **[Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images](https://arxiv.org/abs/2208.02135v1)** - [Code](https://github.com/dogabasaran/lesion-synthesis) (confidence: medium) * **[What is Healthy? Generative Counterfactual Diffusion for Lesion Localization](https://arxiv.org/abs/2207.12268v1)** - [Code](https://github.com/vios-s/diff-scm) (confidence: medium) * **[What Makes for Automatic Reconstruction of Pulmonary Segments](https://arxiv.org/abs/2207.03078v3)** - [Code](https://github.com/m3dv/impulse) (confidence: high) * **[Light-weight spatio-temporal graphs for segmentation and ejection fraction prediction in cardiac ultrasound](https://arxiv.org/abs/2207.02549v1)** - [Code](https://github.com/guybenyosef/echographs) (confidence: high) * **[Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach](https://arxiv.org/abs/2207.00844v1)** - [Code](https://github.com/winstonhutiger/2d_vae_uda_for_3d_sythesis) (confidence: medium) * **[Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans](https://arxiv.org/abs/2206.15445v1)** - [Code](https://github.com/nihaomiao/miccai22_adn) (confidence: high) * **[Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis](https://arxiv.org/abs/2206.15328v2)** - [Code](https://github.com/m3dv/near) (confidence: medium) * **[CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy](https://arxiv.org/abs/2206.14951v1)** - [Code](https://github.com/nadeemlab/cep) (confidence: medium) * **[CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Radiomics and malignancy prediction](https://arxiv.org/abs/2206.14903v1)** - [Code](https://github.com/nadeemlab/cir) (confidence: medium) * **[BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes](https://arxiv.org/abs/2206.14678v1)** - [Code](https://github.com/netanellavisdris/fetalbiometry) (confidence: medium) * **[vMFNet: Compositionality Meets Domain-generalised Segmentation](https://arxiv.org/abs/2206.14538v1)** - [Code](https://github.com/vios-s/vmfnet) (confidence: high) * **[MaNi: Maximizing Mutual Information for Nuclei Cross-Domain Unsupervised Segmentation](https://arxiv.org/abs/2206.14437v1)** - [Code](https://github.com/yashsharma/mani) (confidence: high) * **[Automatic identification of segmentation errors for radiotherapy using geometric learning](https://arxiv.org/abs/2206.13317v1)** - [Code](https://github.com/rrr-uom-projects/contour_auto_qatool) (confidence: high) * **[Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels](https://arxiv.org/abs/2206.07994v1)** - [Code](https://github.com/cityu-aim-group/jcas) (confidence: high) * **[Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images](https://arxiv.org/abs/2206.06665v3)** - [Code](https://github.com/xmed-lab/oeem) (confidence: high) * **[Decoupling Predictions in Distributed Learning for Multi-Center Left Atrial MRI Segmentation](https://arxiv.org/abs/2206.05284v1)** - [Code](https://github.com/key1589745/decouple_predict) (confidence: high) * **[mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation](https://arxiv.org/abs/2206.02425v2)** - [Code](https://github.com/yaozhang93/mmformer) (confidence: high) * **[MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation](https://arxiv.org/abs/2206.01737v2)** - [Code](https://github.com/cherise215/maxstyle) (confidence: high) * **[Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI](https://arxiv.org/abs/2205.01675v1)** - [Code](https://github.com/bchimagine/real_time_fetal_brain_segmentation) (confidence: high) * **[MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels](https://arxiv.org/abs/2203.12454v1)** - [Code](https://github.com/jacobzhaoziyuan/mt-uda) (confidence: high) * **[Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation](https://arxiv.org/abs/2203.08964v2)** - [Code](https://github.com/vinairesearch/point-unet) (confidence: high) * **[CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data](https://arxiv.org/abs/2203.09475v3)** - [Code](https://github.com/hding2455/carts) (confidence: high) * **[ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities](https://arxiv.org/abs/2203.04959v2)** - [Code](https://github.com/han-liu/moddropplusplus) (confidence: high) * **[Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining](https://arxiv.org/abs/2203.01969v3)** - [Code](https://github.com/bbillot/synthseg) (confidence: high) * **[Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2203.01324v3)** - [Code](https://github.com/ycwu1997/ss-net) (confidence: high) * **[Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding](https://arxiv.org/abs/2201.11957v1)** - [Code](https://github.com/lalithjets/global-reasoned-multi-task-model) (confidence: medium) * **[Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task](https://arxiv.org/abs/2201.03777v1)** - [Code](https://github.com/himashi92/vizviva_brats_2021) (confidence: high) * **[QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results](https://arxiv.org/abs/2112.10074v2)** - [Code](https://github.com/ragmeh11/qu-brats) (confidence: high) * **[Virtual Reality for Synergistic Surgical Training and Data Generation](https://arxiv.org/abs/2111.08097v1)** - [Code](https://github.com/lcsr-sickkids/volumetric_drilling) (confidence: medium) * **[Bounding Box Tightness Prior for Weakly Supervised Image Segmentation](https://arxiv.org/abs/2110.00934v1)** - [Code](https://github.com/wangjuan313/wsis-boundingbox) (confidence: high) * **[BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation](https://arxiv.org/abs/2109.12271v2)** - [Code](https://github.com/justatinydot/bitr-unet) (confidence: high) * **[Efficient Context-Aware Network for Abdominal Multi-organ Segmentation](https://arxiv.org/abs/2109.10601v4)** - [Code](https://github.com/shanghai-aitrox-technology/efficientsegmentation) (confidence: high) * **[RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans](https://arxiv.org/abs/2109.09521v1)** - [Code](https://github.com/m3dv/ribseg) (confidence: high) * **[Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge](https://arxiv.org/abs/2109.05409v2)** - [Code](https://github.com/ivadomed/ms-challenge-2021) (confidence: high) * **[Automatic Foot Ulcer Segmentation Using an Ensemble of Convolutional Neural Networks](https://arxiv.org/abs/2109.01408v2)** - [Code](https://github.com/masih4/foot_ulcer_segmentation) (confidence: high) * **[Effective semantic segmentation in Cataract Surgery: What matters most?](https://arxiv.org/abs/2108.06119v1)** - [Code](https://github.com/rvimlab/miccai2021_cataract_semantic_segmentation) (confidence: high) * **[A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis](https://arxiv.org/abs/2108.05930v1)** - [Code](https://github.com/jlianglab/benchmarktransferlearning) (confidence: medium) * **[Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation](https://arxiv.org/abs/2108.05269v1)** - [Code](https://github.com/jianningli/voxel_rearrangement) (confidence: high) * **[Automatic Polyp Segmentation via Multi-scale Subtraction Network](https://arxiv.org/abs/2108.05082v1)** - [Code](https://github.com/xiaoqi-zhao-dlut/msnet) (confidence: high) * **[MixLacune: Segmentation of lacunes of presumed vascular origin](https://arxiv.org/abs/2108.02483v1)** - [Code](https://github.com/hjkuijf/mixlacune) (confidence: high) * **[MixMicrobleedNet: segmentation of cerebral microbleeds using nnU-Net](https://arxiv.org/abs/2108.01389v1)** - [Code](https://github.com/hjkuijf/mixmicrobleednet) (confidence: high) * **[Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation](https://arxiv.org/abs/2107.10100v1)** - [Code](https://github.com/gaozhitong/sp_guided_noisy_label_seg) (confidence: high) * **[Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation](https://arxiv.org/abs/2107.06941v2)** - [Code](https://github.com/cardio-ai/detcyclegan_pytorch) (confidence: medium) * **[Few-Shot Domain Adaptation with Polymorphic Transformers](https://arxiv.org/abs/2107.04805v1)** - [Code](https://github.com/askerlee/segtran) (confidence: medium) * **[Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation](https://arxiv.org/abs/2107.03887v1)** - [Code](https://github.com/shuowang26/srheart) (confidence: high) * **[Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation](https://arxiv.org/abs/2107.03846v2)** - [Code](https://github.com/lucasfidon/label-set-loss-functions) (confidence: high) * **[Controllable cardiac synthesis via disentangled anatomy arithmetic](https://arxiv.org/abs/2107.01748v1)** - [Code](https://github.com/vios-s/daa-gan) (confidence: medium) * **[Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation](https://arxiv.org/abs/2107.00977v1)** - [Code](https://github.com/hreynaud/uvt) (confidence: medium) * **[UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation](https://arxiv.org/abs/2107.00781v2)** - [Code](https://github.com/yhygao/utnet) (confidence: high) * **[Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation](https://arxiv.org/abs/2107.00583v3)** - [Code](https://github.com/reubendo/inextremis) (confidence: high) * **[FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos](https://arxiv.org/abs/2106.12522v2)** - [Code](https://github.com/nadeemlab/cep) (confidence: high) * **[Quality-Aware Memory Network for Interactive Volumetric Image Segmentation](https://arxiv.org/abs/2106.10686v2)** - [Code](https://github.com/0liliulei/mem3d) (confidence: high) * **[nnDetection: A Self-configuring Method for Medical Object Detection](https://arxiv.org/abs/2106.00817v2)** - [Code](https://github.com/mic-dkfz/nndetection) (confidence: medium) * **[About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations](https://arxiv.org/abs/2105.14117v4)** - [Code](https://github.com/dmitriishubin/variance-aware-training) (confidence: medium) * **[Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning](https://arxiv.org/abs/2105.12722v2)** - [Code](https://github.com/pakheiyeung/sli2vol) (confidence: high) * **[A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections](https://arxiv.org/abs/2105.11239v1)** - [Code](https://github.com/fepegar/ressegijcars) (confidence: high) * **[TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation](https://arxiv.org/abs/2105.08993v1)** - [Code](https://github.com/2165998/targan) (confidence: medium) * **[Progressively Normalized Self-Attention Network for Video Polyp Segmentation](https://arxiv.org/abs/2105.08468v2)** - [Code](https://github.com/gewelsji/pns-net) (confidence: high) * **[CateNorm: Categorical Normalization for Robust Medical Image Segmentation](https://arxiv.org/abs/2103.15858v2)** - [Code](https://github.com/lambert-x/catenorm) (confidence: high) * **[Medical Transformer: Gated Axial-Attention for Medical Image Segmentation](https://arxiv.org/abs/2102.10662v2)** - [Code](https://github.com/jeya-maria-jose/medical-transformer) (confidence: high) * **[Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images](https://arxiv.org/abs/2102.10446v1)** - [Code](https://github.com/iantsen/hecktor) (confidence: high) * **[Loss Ensembles for Extremely Imbalanced Segmentation](https://arxiv.org/abs/2101.10815v1)** - [Code](https://github.com/junma11/adam2020) (confidence: high) * **[Exploring Large Context for Cerebral Aneurysm Segmentation](https://arxiv.org/abs/2012.15136v1)** - [Code](https://github.com/junma11/cada2020) (confidence: high) * **[Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation](https://arxiv.org/abs/2012.13871v1)** - [Code](https://github.com/junma11/hm_dataaug) (confidence: high) * **[Deep learning based registration using spatial gradients and noisy segmentation labels](https://arxiv.org/abs/2010.10897v2)** - [Code](https://github.com/theoest/abdominal_registration) (confidence: high) | [Code2](https://github.com/theoest/hippocampus_registration) * **[Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation](https://arxiv.org/abs/2010.07411v2)** - [Code](https://github.com/elchiou/da) (confidence: high) * **[Selective Information Passing for MR/CT Image Segmentation](https://arxiv.org/abs/2010.04920v1)** - [Code](https://github.com/ahukui/sipnet) (confidence: high) * **[KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation](https://arxiv.org/abs/2010.01663v2)** - [Code](https://github.com/jeya-maria-jose/kiu-net-pytorch) (confidence: high) * **[3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology](https://arxiv.org/abs/2009.05596v1)** - [Code](https://github.com/htregidgo/dissectionphotovolumes) (confidence: high) * **[INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs](https://arxiv.org/abs/2008.10418v1)** - [Code](https://github.com/jacenkow/inside) (confidence: high) * **[Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation](https://arxiv.org/abs/2007.10033v1)** - [Code](https://github.com/neuro-ml/inverse_weighting) (confidence: high) * **[Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration](https://arxiv.org/abs/2007.06959v1)** - [Code](https://github.com/jlianglab/semanticgenesis) (confidence: medium) * **[Anatomical Data Augmentation via Fluid-based Image Registration](https://arxiv.org/abs/2007.02447v1)** - [Code](https://github.com/uncbiag/easyreg) (confidence: medium) * **[Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains](https://arxiv.org/abs/2007.02035v1)** - [Code](https://github.com/liuquande/saml) (confidence: high) * **[Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet](https://arxiv.org/abs/2006.15954v2)** - [Code](https://github.com/raykoooo/cac-unet) (confidence: high) * **[MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation](https://arxiv.org/abs/2006.15573v2)** - [Code](https://github.com/xzluo97/mvmm-regnet) (confidence: medium) * **[AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation](https://arxiv.org/abs/2006.14858v1)** - [Code](https://github.com/meclabtuda/autosnap) (confidence: medium) * **[Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning](https://arxiv.org/abs/2006.07694v1)** - [Code](https://github.com/dial-rpi/freehandusrecon) (confidence: medium) * **[KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations](https://arxiv.org/abs/2006.04878v2)** - [Code](https://github.com/jeya-maria-jose/kiu-net-pytorch) (confidence: high) * **[Boundary-assisted Region Proposal Networks for Nucleus Segmentation](https://arxiv.org/abs/2006.02695v1)** - [Code](https://github.com/csccsccsccsc/brpnet) (confidence: high) * **[Segmentation Loss Odyssey](https://arxiv.org/abs/2005.13449v1)** - [Code](https://github.com/junma11/segloss) (confidence: high) * **[Weakly supervised multiple instance learning histopathological tumor segmentation](https://arxiv.org/abs/2004.05024v4)** - [Code](https://github.com/marvinler/tcga_segmentation) (confidence: high) * **[RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation](https://arxiv.org/abs/2002.12470v1)** - [Code](https://github.com/tinymilky/rsanet) (confidence: high) * **[VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images](https://arxiv.org/abs/2001.09193v6)** - [Code](https://github.com/anjany/verse) (confidence: high) * **[Regression and Learning with Pixel-wise Attention for Retinal Fundus Glaucoma Segmentation and Detection](https://arxiv.org/abs/2001.01815v1)** - [Code](https://github.com/cswin/rlpa) (confidence: high) * **[Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response](https://arxiv.org/abs/1911.13077v1)** - [Code](https://github.com/naivete5656/wsispdr) (confidence: high) * **[Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data](https://arxiv.org/abs/1909.09716v1)** - [Code](https://github.com/horsepurve/stylesegor) (confidence: high) * **[Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis](https://arxiv.org/abs/1908.06912v1)** - [Code](https://github.com/mrgiovanni/modelsgenesis) (confidence: medium) * **[Multi-step Cascaded Networks for Brain Tumor Segmentation](https://arxiv.org/abs/1908.05887v3)** - [Code](https://github.com/johnleehit/brats2019) (confidence: high) * **[MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation](https://arxiv.org/abs/1908.04373v1)** - [Code](https://github.com/rsummers11/cadlab) (confidence: high) * **[Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation](https://arxiv.org/abs/1907.13124v1)** - [Code](https://github.com/utkuozbulak/adaptive-segmentation-mask-attack) (confidence: high) * **[NoduleNet: Decoupled False Positive Reductionfor Pulmonary Nodule Detection and Segmentation](https://arxiv.org/abs/1907.11320v1)** - [Code](https://github.com/uci-cbcl/nodulenet) (confidence: high) * **[Attention Guided Network for Retinal Image Segmentation](https://arxiv.org/abs/1907.12930v3)** - [Code](https://github.com/hzfu/agnet) (confidence: high) * **[ET-Net: A Generic Edge-aTtention Guidance Network for Medical Image Segmentation](https://arxiv.org/abs/1907.10936v1)** - [Code](https://github.com/zzzjzzz/etnet) (confidence: high) * **[Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks](https://arxiv.org/abs/1907.10931v1)** - [Code](https://github.com/multimodallearning/pdd_net) (confidence: medium) * **[Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes](https://arxiv.org/abs/1907.09140v2)** - [Code](https://github.com/yijingru/kg_instance_segmentation) (confidence: high) * **[Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video](https://arxiv.org/abs/1907.07899v1)** - [Code](https://github.com/keyuncheng/mf-tapnet) (confidence: high) * **[X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies](https://arxiv.org/abs/1907.07000v2)** - [Code](https://github.com/andrewsher/x-net) (confidence: high) * **[Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation](https://arxiv.org/abs/1906.11143v2)** - [Code](https://github.com/emmaw8/beal) (confidence: high) * **[`Project & Excite' Modules for Segmentation of Volumetric Medical Scans](https://arxiv.org/abs/1906.04649v2)** - [Code](https://github.com/ai-med/squeeze_and_excitation) (confidence: high) * **[Multi-Task Learning for Left Atrial Segmentation on GE-MRI](https://arxiv.org/abs/1810.13205v1)** - [Code](https://github.com/cherise215/atria_segmentation_2018) (confidence: high) * **[CapsDeMM: Capsule network for Detection of Munro's Microabscess in skin biopsy images](https://arxiv.org/abs/1808.06428v2)** - [Code](https://github.com/anabik/capsdemm) (confidence: medium) * **[AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy](https://arxiv.org/abs/1808.05238v2)** - [Code](https://github.com/wentaozhu/anatomynet-for-anatomical-segmentation) (confidence: high) * **[Rotation Equivariant CNNs for Digital Pathology](https://arxiv.org/abs/1806.03962v1)** - [Code](https://github.com/basveeling/keras_gcnn) (confidence: medium) | [Code2](https://github.com/basveeling/pcam) * **[Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks](https://arxiv.org/abs/1804.08024v1)** - [Code](https://github.com/ternaus/angiodysplasia-segmentatio) (confidence: high) * **[HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation](https://arxiv.org/abs/1804.02967v2)** - [Code](https://github.com/josedolz/hyperdensenet) (confidence: high) * **[Factorised spatial representation learning: application in semi-supervised myocardial segmentation](https://arxiv.org/abs/1803.07031v2)** - [Code](https://github.com/agis85/spatial_factorisation) (confidence: high) * **[Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning](https://arxiv.org/abs/1803.01207v2)** - [Code](https://github.com/ternaus/robot-surgery-segmentation) (confidence: high) * **[Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields](https://arxiv.org/abs/1610.02177v1)** - [Code](https://github.com/ibbm/cascaded-fcn) (confidence: high) ## 🔧 Reconstruction *This list is automatically generated. See any issues? Please open a pull request!* * **[Anatomy-Grounded Synthetic Coronary Angiography for Geometry-Informed Multi-View Matching](https://arxiv.org/abs/2606.28474v1)** - [Code](https://github.com/medipixel/gimm) (confidence: medium) * **[NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction](https://arxiv.org/abs/2606.24087v1)** - [Code](https://github.com/y-research-sbu/neurosonic) (confidence: high) * **[MaRS: Robust Out-of-Distribution Detection via Mahalanobis Residual Scoring](https://arxiv.org/abs/2606.22649v2)** - [Code](https://github.com/francescodisalvo05/mars) (confidence: medium) * **[When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning](https://arxiv.org/abs/2606.19827v1)** - [Code](https://github.com/labhai/adaptive-binning) (confidence: medium) * **[Test-Time Adaptation in Optical Coherence Tomography Using Trajectory-Aligned Time-Independent Flow](https://arxiv.org/abs/2606.18876v2)** - [Code](https://github.com/veit21/tta-flow) (confidence: medium) * **[Propagating Structural Guidance: Synthesizing Fluorescein Angiography from Fundus Images and Sparse OCT Scans](https://arxiv.org/abs/2606.16234v1)** - [Code](https://github.com/while-plus/oct-guide-ffa-syn) (confidence: medium) * **[Learning Directional Semantic Transitions for Longitudinal Chest X-ray Analysis](https://arxiv.org/abs/2606.15938v1)** - [Code](https://github.com/rpidial/protrans) (confidence: medium) * **[Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation](https://arxiv.org/abs/2605.25402v3)** - [Code](https://github.com/zhcz328/anaus) (confidence: medium) * **[ImPartial: Multi-channel Whole-Cell Segmentation using Partial Annotations](https://arxiv.org/abs/2605.24128v1)** - [Code](https://github.com/nadeemlab/impartial) (confidence: high) * **[Defining Robust Ultrasound Quality Metrics via an Ultrasound Foundation Model](https://arxiv.org/abs/2604.19512v2)** - [Code](https://github.com/sextant-fable/us-metrics) (confidence: medium) * **[EchoLVFM: One-Step Video Generation via Latent Flow Matching for Echocardiogram Synthesis](https://arxiv.org/abs/2603.13967v1)** - [Code](https://github.com/engemmanuel/echolvfm) (confidence: medium) * **[TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration](https://arxiv.org/abs/2512.14550v1)** - [Code](https://github.com/yaziwel/tat) (confidence: high) * **[US-X Complete: A Multi-Modal Approach to Anatomical 3D Shape Recovery](https://arxiv.org/abs/2511.15600v1)** - [Code](https://github.com/miruna20/us-x-complete) (confidence: medium) * **[Benchmark-Ready 3D Anatomical Shape Classification](https://arxiv.org/abs/2511.01613v1)** - [Code](https://github.com/tomaskrsicka/medshapenet19-pspooling) (confidence: medium) * **[The Missing Piece: A Case for Pre-Training in 3D Medical Object Detection](https://arxiv.org/abs/2509.15947v1)** - [Code](https://github.com/mic-dkfz/nndetection-finetuning) (confidence: medium) * **[UltrON: Ultrasound Occupancy Networks](https://arxiv.org/abs/2509.08991v1)** - [Code](https://github.com/magdalena-wysocki/ultron) (confidence: medium) * **[XOCT: Enhancing OCT to OCTA Translation via Cross-Dimensional Supervised Multi-Scale Feature Learning](https://arxiv.org/abs/2509.07455v1)** - [Code](https://github.com/uci-cbcl/xoct) (confidence: high) * **[Neural Proteomics Fields for Super-resolved Spatial Proteomics Prediction](https://arxiv.org/abs/2508.17389v1)** - [Code](https://github.com/bokai-zhao/npf) (confidence: high) * **[Tooth-Diffusion: Guided 3D CBCT Synthesis with Fine-Grained Tooth Conditioning](https://arxiv.org/abs/2508.14276v1)** - [Code](https://github.com/djafar1/tooth-diffusion) (confidence: medium) * **[Comparing Conditional Diffusion Models for Synthesizing Contrast-Enhanced Breast MRI from Pre-Contrast Images](https://arxiv.org/abs/2508.13776v2)** - [Code](https://github.com/sebastibar/conditional-diffusion-breast-mri) (confidence: medium) * **[HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters](https://arxiv.org/abs/2508.13026v1)** - [Code](https://github.com/ruru-xu/hieradaptmr) (confidence: high) * **[Cross-view Generalized Diffusion Model for Sparse-view CT Reconstruction](https://arxiv.org/abs/2508.10313v1)** - [Code](https://github.com/xmed-lab/cvg-diff) (confidence: high) * **[Adaptive k-space Radial Sampling for Cardiac MRI with Reinforcement Learning](https://arxiv.org/abs/2508.04727v2)** - [Code](https://github.com/ruru-xu/rl-kspace-radial-sampling) (confidence: medium) * **[VidFuncta: Towards Generalizable Neural Representations for Ultrasound Videos](https://arxiv.org/abs/2507.21863v1)** - [Code](https://github.com/juliawolleb/vidfuncta_public) (confidence: medium) * **[Focus on Texture: Rethinking Pre-training in Masked Autoencoders for Medical Image Classification](https://arxiv.org/abs/2507.10869v1)** - [Code](https://github.com/chetanmadan/glcm-mae) (confidence: high) * **[Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructions](https://arxiv.org/abs/2507.00670v1)** - [Code](https://github.com/nikolasmorshuis/sdr) (confidence: high) * **[Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound](https://arxiv.org/abs/2506.23538v2)** - [Code](https://github.com/yuhoo0302/cua-us) (confidence: high) * **[SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting](https://arxiv.org/abs/2506.23309v2)** - [Code](https://github.com/lastbasket/surgtpgs) (confidence: medium) * **[Endo-4DGX: Robust Endoscopic Scene Reconstruction and Illumination Correction with Gaussian Splatting](https://arxiv.org/abs/2506.23308v1)** - [Code](https://github.com/lastbasket/endo-4dgx) (confidence: high) * **[DIGS: Dynamic CBCT Reconstruction using Deformation-Informed 4D Gaussian Splatting and a Low-Rank Free-Form Deformation Model](https://arxiv.org/abs/2506.22280v1)** - [Code](https://github.com/yuliang-huang/digs) (confidence: high) * **[FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation](https://arxiv.org/abs/2506.04956v1)** - [Code](https://github.com/yaziwel/feat) (confidence: medium) * **[Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays](https://arxiv.org/abs/2505.17311v1)** - [Code](https://github.com/nth221/diff3m) (confidence: medium) * **[VesselGPT: Autoregressive Modeling of Vascular Geometry](https://arxiv.org/abs/2505.13318v2)** - [Code](https://github.com/lia-ditella/vesselgpt-miccai) (confidence: medium) * **[Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge](https://arxiv.org/abs/2503.24306v1)** - [Code](https://github.com/athaddius/stirmetrics) (confidence: medium) * **[Automatic quality control in multi-centric fetal brain MRI super-resolution reconstruction](https://arxiv.org/abs/2503.10156v4)** - [Code](https://github.com/medical-image-analysis-laboratory/fetmrqc_sr) (confidence: high) * **[Generating Novel Brain Morphology by Deforming Learned Templates](https://arxiv.org/abs/2503.03778v3)** - [Code](https://github.com/alanqrwang/morphldm) (confidence: medium) * **[DiffuseReg: Denoising Diffusion Model for Obtaining Deformation Fields in Unsupervised Deformable Image Registration](https://arxiv.org/abs/2410.05234v1)** - [Code](https://github.com/yutazhuo/diffusereg) (confidence: high) * **[3DGR-CAR: Coronary artery reconstruction from ultra-sparse 2D X-ray views with a 3D Gaussians representation](https://arxiv.org/abs/2410.00404v1)** - [Code](https://github.com/windrise/3dgr-car) (confidence: high) * **[Accelerated Multi-Contrast MRI Reconstruction via Frequency and Spatial Mutual Learning](https://arxiv.org/abs/2409.14113v1)** - [Code](https://github.com/qic999/fsmnet) (confidence: high) * **[RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction](https://arxiv.org/abs/2408.07325v1)** - [Code](https://github.com/chenhbo/rocosdf) (confidence: high) * **[HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training](https://arxiv.org/abs/2408.05815v1)** - [Code](https://github.com/fenghetan9/hyspark) (confidence: medium) * **[A Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery](https://arxiv.org/abs/2408.04426v1)** - [Code](https://github.com/epsilon404/surgicalnerf) (confidence: high) * **[Spatial-Division Augmented Occupancy Field for Bone Shape Reconstruction from Biplanar X-Rays](https://arxiv.org/abs/2407.15433v1)** - [Code](https://github.com/xmed-lab/sdaof) (confidence: high) * **[WiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration](https://arxiv.org/abs/2407.13426v1)** - [Code](https://github.com/x-xc/winet) (confidence: medium) * **[DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2407.09918v1)** - [Code](https://github.com/cuhk-aim-group/diffrect) (confidence: medium) * **[Let Me DeCode You: Decoder Conditioning with Tabular Data](https://arxiv.org/abs/2407.09437v1)** - [Code](https://github.com/sanoscience/decode) (confidence: medium) * **[Region Attention Transformer for Medical Image Restoration](https://arxiv.org/abs/2407.09268v1)** - [Code](https://github.com/yaziwel/region-attention-transformer-for-medical-image-restoration) (confidence: high) * **[FD-SOS: Vision-Language Open-Set Detectors for Bone Fenestration and Dehiscence Detection from Intraoral Images](https://arxiv.org/abs/2407.09088v1)** - [Code](https://github.com/xmed-lab/fd-sos) (confidence: medium) * **[Nonrigid Reconstruction of Freehand Ultrasound without a Tracker](https://arxiv.org/abs/2407.05767v2)** - [Code](https://github.com/qili111/nr-rec-fus) (confidence: high) * **[Generalized Robust Fundus Photography-based Vision Loss Estimation for High Myopia](https://arxiv.org/abs/2407.03699v2)** - [Code](https://github.com/yanzipei/vf_red) (confidence: medium) * **[An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis](https://arxiv.org/abs/2407.03018v1)** - [Code](https://github.com/xmed-lab/geca) (confidence: medium) * **[Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction](https://arxiv.org/abs/2407.02918v1)** - [Code](https://github.com/wrld/free-surgs) (confidence: high) * **[Learning 3D Gaussians for Extremely Sparse-View Cone-Beam CT Reconstruction](https://arxiv.org/abs/2407.01090v2)** - [Code](https://github.com/xmed-lab/dif-gaussian) (confidence: high) * **[Resolving Variable Respiratory Motion From Unsorted 4D Computed Tomography](https://arxiv.org/abs/2407.00665v1)** - [Code](https://github.com/yuliang-huang/4dct-irregular-motion) (confidence: medium) * **[EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy](https://arxiv.org/abs/2406.13705v2)** - [Code](https://github.com/longbai1006/endouic) (confidence: medium) * **[All-In-One Medical Image Restoration via Task-Adaptive Routing](https://arxiv.org/abs/2405.19769v2)** - [Code](https://github.com/yaziwel/all-in-one-medical-image-restoration-via-task-adaptive-routing) (confidence: high) * **[Deform3DGS: Flexible Deformation for Fast Surgical Scene Reconstruction with Gaussian Splatting](https://arxiv.org/abs/2405.17835v3)** - [Code](https://github.com/jinlab-imvr/deform3dgs) (confidence: high) * **[EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera](https://arxiv.org/abs/2405.08672v1)** - [Code](https://github.com/beileicui/endodac) (confidence: medium) * **[Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Model](https://arxiv.org/abs/2404.17357v4)** - [Code](https://github.com/xylonxu01/tfs-diff) (confidence: high) * **[Metric-Guided Conformal Bounds for Probabilistic Image Reconstruction](https://arxiv.org/abs/2404.15274v4)** - [Code](https://github.com/matthewyccheung/conformal-metric) (confidence: high) * **[Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective](https://arxiv.org/abs/2403.09303v3)** - [Code](https://github.com/caiyu6666/ae4ad) (confidence: high) * **[$TrIND$: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields](https://arxiv.org/abs/2403.08974v3)** - [Code](https://github.com/sinashish/treediffusion) (confidence: high) * **[Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI](https://arxiv.org/abs/2403.08298v2)** - [Code](https://github.com/hannaheichhorn/phimo) (confidence: high) * **[MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation](https://arxiv.org/abs/2402.17725v2)** - [Code](https://github.com/hananshafi/medcontext) (confidence: medium) * **[EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting](https://arxiv.org/abs/2401.11535v3)** - [Code](https://github.com/hku-medai/endogs) (confidence: high) * **[Surgical-DINO: Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery](https://arxiv.org/abs/2401.06013v2)** - [Code](https://github.com/beileicui/surgicaldino) (confidence: medium) * **[DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models](https://arxiv.org/abs/2312.04853v1)** - [Code](https://github.com/xmed-lab/diffcmr) (confidence: high) * **[SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models](https://arxiv.org/abs/2310.01799v2)** - [Code](https://github.com/nvlabs/smrd) (confidence: high) * **[Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head](https://arxiv.org/abs/2309.17143v1)** - [Code](https://github.com/5k5000/cldetection2023) (confidence: high) * **[NoSENSE: Learned unrolled cardiac MRI reconstruction without explicit sensitivity maps](https://arxiv.org/abs/2309.15608v2)** - [Code](https://github.com/fzimmermann89/cmrxrecon) (confidence: high) * **[On the Localization of Ultrasound Image Slices within Point Distribution Models](https://arxiv.org/abs/2309.00372v1)** - [Code](https://github.com/vuenc/slice-to-shape) (confidence: medium) * **[Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction](https://arxiv.org/abs/2308.10157v1)** - [Code](https://github.com/show-han/pet-reconstruction) (confidence: high) * **[DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction](https://arxiv.org/abs/2308.09223v1)** - [Code](https://github.com/hexiaoxiao-cs/dmcvr) (confidence: high) * **[Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation](https://arxiv.org/abs/2308.07731v1)** - [Code](https://github.com/xmed-lab/cpr) (confidence: medium) * **[SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction](https://arxiv.org/abs/2308.04262v1)** - [Code](https://github.com/rahul-gs-16/sdlformer) (confidence: high) * **[DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation](https://arxiv.org/abs/2308.02959v1)** - [Code](https://github.com/mindflow-institue/dermosegdiff) (confidence: medium) * **[Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection](https://arxiv.org/abs/2308.01639v1)** - [Code](https://github.com/mediabrain-sjtu/ecgad) (confidence: high) * **[SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation](https://arxiv.org/abs/2307.12591v1)** - [Code](https://github.com/ucsc-vlaa/swinmm) (confidence: medium) * **[SwIPE: Efficient and Robust Medical Image Segmentation with Implicit Patch Embeddings](https://arxiv.org/abs/2307.12429v2)** - [Code](https://github.com/charzharr/miccai23-swipe-implicit-segmentation) (confidence: medium) * **[ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising](https://arxiv.org/abs/2307.12225v1)** - [Code](https://github.com/hao1635/ascon) (confidence: high) * **[EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos](https://arxiv.org/abs/2307.11307v2)** - [Code](https://github.com/ruyi-zha/endosurf) (confidence: high) * **[FreeSeed: Frequency-band-aware and Self-guided Network for Sparse-view CT Reconstruction](https://arxiv.org/abs/2307.05890v1)** - [Code](https://github.com/masaaki-75/freeseed) (confidence: high) * **[Unsupervised 3D out-of-distribution detection with latent diffusion models](https://arxiv.org/abs/2307.03777v1)** - [Code](https://github.com/marksgraham/ddpm-ood) (confidence: high) * **[Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation](https://arxiv.org/abs/2307.03008v3)** - [Code](https://github.com/j-morano/multimodal-ssl-fpn) (confidence: high) * **[LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion](https://arxiv.org/abs/2307.02452v2)** - [Code](https://github.com/longbai1006/llcaps) (confidence: medium) * **[Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks](https://arxiv.org/abs/2307.00899v1)** - [Code](https://github.com/matt-baugh/many-tasks-make-light-work) (confidence: medium) * **[A denoised Mean Teacher for domain adaptive point cloud registration](https://arxiv.org/abs/2306.14749v2)** - [Code](https://github.com/multimodallearning/denoised_mt_pcd_reg) (confidence: medium) * **[CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?](https://arxiv.org/abs/2306.14350v1)** - [Code](https://github.com/ayanglab/cdiffmr) (confidence: high) * **[MEPNet: A Model-Driven Equivariant Proximal Network for Joint Sparse-View Reconstruction and Metal Artifact Reduction in CT Images](https://arxiv.org/abs/2306.14274v1)** - [Code](https://github.com/hongwang01/mepnet) (confidence: high) * **[Learning Deep Intensity Field for Extremely Sparse-View CBCT Reconstruction](https://arxiv.org/abs/2303.06681v3)** - [Code](https://github.com/xmed-lab/dif-net) (confidence: high) * **[Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays](https://arxiv.org/abs/2303.06500v3)** - [Code](https://github.com/ibrahimethemhamamci/hierarchicaldet) (confidence: medium) * **[Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation](https://arxiv.org/abs/2303.06040v3)** - [Code](https://github.com/mathpluscode/imgx-diffseg) (confidence: medium) * **[Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence](https://arxiv.org/abs/2209.13818v1)** - [Code](https://github.com/laowangbobo/residual_mlp_cnn_mixer) (confidence: high) * **[Attentive Symmetric Autoencoder for Brain MRI Segmentation](https://arxiv.org/abs/2209.08887v1)** - [Code](https://github.com/lhaof/asa) (confidence: high) * **[Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://arxiv.org/abs/2209.06861v1)** - [Code](https://github.com/davecasp/flowssm) (confidence: medium) * **[Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging](https://arxiv.org/abs/2208.12737v1)** - [Code](https://github.com/v715/diffdrr) (confidence: medium) * **[Unsupervised Anomaly Localization with Structural Feature-Autoencoders](https://arxiv.org/abs/2208.10992v1)** - [Code](https://github.com/felime/feature-autoencoder) (confidence: medium) * **[Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN](https://arxiv.org/abs/2208.03008v1)** - [Code](https://github.com/yongsongh/aidsrgan-miccai2022) (confidence: high) * **[Gigapixel Whole-Slide Images Classification using Locally Supervised Learning](https://arxiv.org/abs/2207.08267v2)** - [Code](https://github.com/cvlab-stonybrook/local_learning_wsi) (confidence: medium) * **[What Makes for Automatic Reconstruction of Pulmonary Segments](https://arxiv.org/abs/2207.03078v3)** - [Code](https://github.com/m3dv/impulse) (confidence: high) * **[Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI](https://arxiv.org/abs/2207.02390v1)** - [Code](https://github.com/ayanglab/sdaut) (confidence: high) * **[vMFNet: Compositionality Meets Domain-generalised Segmentation](https://arxiv.org/abs/2206.14538v1)** - [Code](https://github.com/vios-s/vmfnet) (confidence: high) * **[RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans](https://arxiv.org/abs/2206.06253v1)** - [Code](https://github.com/smilenaxx/rplhr-ct) (confidence: high) * **[Poisson2Sparse: Self-Supervised Poisson Denoising From a Single Image](https://arxiv.org/abs/2206.01856v2)** - [Code](https://github.com/tacalvin/poisson2sparse) (confidence: high) * **[Free Lunch for Surgical Video Understanding by Distilling Self-Supervisions](https://arxiv.org/abs/2205.09292v2)** - [Code](https://github.com/xmed-lab/distillingself) (confidence: medium) * **[Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI](https://arxiv.org/abs/2205.01675v1)** - [Code](https://github.com/bchimagine/real_time_fetal_brain_segmentation) (confidence: medium) * **[Progressive Subsampling for Oversampled Data - Application to Quantitative MRI](https://arxiv.org/abs/2203.09268v5)** - [Code](https://github.com/sbb-gh/prosub) (confidence: medium) * **[Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and no Retraining](https://arxiv.org/abs/2203.01969v3)** - [Code](https://github.com/bbillot/synthseg) (confidence: medium) * **[Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation](https://arxiv.org/abs/2108.05269v1)** - [Code](https://github.com/jianningli/voxel_rearrangement) (confidence: medium) * **[Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations](https://arxiv.org/abs/2107.10839v1)** - [Code](https://github.com/fkong7/heartffdnet) (confidence: medium) * **[3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images](https://arxiv.org/abs/2107.09700v1)** - [Code](https://github.com/sh4174/3dstylegan) (confidence: medium) * **[Frequency-Supervised MR-to-CT Image Synthesis](https://arxiv.org/abs/2107.08962v1)** - [Code](https://github.com/shizenglin/frequency-supervised-mr-to-ct-image-synthesis) (confidence: medium) * **[Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation](https://arxiv.org/abs/2107.03887v1)** - [Code](https://github.com/shuowang26/srheart) (confidence: high) * **[Detecting Outliers with Poisson Image Interpolation](https://arxiv.org/abs/2107.02622v1)** - [Code](https://github.com/jemtan/pii) (confidence: medium) * **[Uncertainty-Guided Progressive GANs for Medical Image Translation](https://arxiv.org/abs/2106.15542v2)** - [Code](https://github.com/explainableml/uncerguidedi2i) (confidence: high) * **[Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI](https://arxiv.org/abs/2106.13188v1)** - [Code](https://github.com/mengweiren/q-space-conditioned-dwi-synthesis) (confidence: medium) * **[Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning](https://arxiv.org/abs/2105.12722v2)** - [Code](https://github.com/pakheiyeung/sli2vol) (confidence: medium) * **[3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology](https://arxiv.org/abs/2009.05596v1)** - [Code](https://github.com/htregidgo/dissectionphotovolumes) (confidence: high) * **[Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images](https://arxiv.org/abs/2007.08340v2)** - [Code](https://github.com/camma-public/orpose-depth) (confidence: medium) * **[Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration](https://arxiv.org/abs/2007.06959v1)** - [Code](https://github.com/jlianglab/semanticgenesis) (confidence: high) * **[Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterations](https://arxiv.org/abs/2006.15271v3)** - [Code](https://github.com/edongdongchen/pgd-net) (confidence: high) * **[Sensorless Freehand 3D Ultrasound Reconstruction via Deep Contextual Learning](https://arxiv.org/abs/2006.07694v1)** - [Code](https://github.com/dial-rpi/freehandusrecon) (confidence: high) * **[Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment](https://arxiv.org/abs/2003.08502v2)** - [Code](https://github.com/lppllppl920/densereconstruction-pytorch) (confidence: medium) * **[VS-Net: Variable splitting network for accelerated parallel MRI reconstruction](https://arxiv.org/abs/1907.10033v1)** - [Code](https://github.com/j-duan/vs-net) (confidence: high) ## 🏷️ Classification *This list is automatically generated. See any issues? Please open a pull request!* * **[MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching](https://arxiv.org/abs/2606.28537v1)** - [Code](https://github.com/xypb/mammoflow) (confidence: medium) * **[Pulmonary Embolism Risk Stratification from CTPA and Medical Records: Vascular Graphs Are Not All You Need](https://arxiv.org/abs/2606.25956v2)** - [Code](https://github.com/creatis-myriad/genesis) (confidence: medium) * **[FunPiQ: A New Benchmark for Pixel-Level Quality Assessment in Fundus Images](https://arxiv.org/abs/2606.25915v1)** - [Code](https://github.com/penway/funpiq) (confidence: high) * **[Beyond Visual Forensics: Auditing Multimodal Robustness for Synthetic Medical Image Detection](https://arxiv.org/abs/2606.25375v1)** - [Code](https://github.com/chiuhaohao/beyond-visual-forensics) (confidence: high) * **[From Point Estimates to Distributions: GMM Pooling for MIL in Preterm Birth Prediction](https://arxiv.org/abs/2606.23005v1)** - [Code](https://github.com/hussainalasmawi/gmm_pooling) (confidence: medium) * **[Evo-RAD: Navigating Rare Retinal Disease Diagnosis via Self-Evolving Agentic Retrieval](https://arxiv.org/abs/2606.22955v1)** - [Code](https://github.com/sdh-lab/evo-rad) (confidence: medium) * **[MaRS: Robust Out-of-Distribution Detection via Mahalanobis Residual Scoring](https://arxiv.org/abs/2606.22649v2)** - [Code](https://github.com/francescodisalvo05/mars) (confidence: high) * **[Surgical Anatomy Recognition with Context Learning using Foundation Representations](https://arxiv.org/abs/2606.22124v1)** - [Code](https://github.com/timjaspers0801/atlas) (confidence: high) * **[One-Shot Data Selection for Medical Image Classification via Graph Coverage](https://arxiv.org/abs/2606.22002v1)** - [Code](https://github.com/zahiriddin-rustamov/graph-coverage-selection) (confidence: high) * **[MedTS-TTT: Test-Time Training for Medical Time Series Classification](https://arxiv.org/abs/2606.21329v1)** - [Code](https://github.com/mingzhi-c/medts-ttt) (confidence: high) * **[A Neurosymbolic Framework for Interpretable Skeleton-Based Seizure Detection via Concept-Driven Logical Reasoning](https://arxiv.org/abs/2606.21252v1)** - [Code](https://github.com/mr-talhailyas/cdsd) (confidence: high) * **[OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classification](https://arxiv.org/abs/2606.19838v1)** - [Code](https://github.com/labhai/otcha) (confidence: high) * **[When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning](https://arxiv.org/abs/2606.19827v1)** - [Code](https://github.com/labhai/adaptive-binning) (confidence: medium) * **[A Multi-Center Benchmark for Abdominal Disease Diagnosis and Report Generation from Non-Contrast CT](https://arxiv.org/abs/2606.16991v1)** - [Code](https://github.com/xmed-lab/trials-report) (confidence: medium) * **[3D Classification of Paramagnetic Rim Lesions in Multiple Sclerosis via Asymmetric QSM-FLAIR Modeling](https://arxiv.org/abs/2606.16756v1)** - [Code](https://github.com/veronicapignedoli/frodo) (confidence: high) * **[Learning Directional Semantic Transitions for Longitudinal Chest X-ray Analysis](https://arxiv.org/abs/2606.15938v1)** - [Code](https://github.com/rpidial/protrans) (confidence: medium) * **[Genetically Aligned Patient Representations Improve Hematological Diagnosis](https://arxiv.org/abs/2605.29980v1)** - [Code](https://github.com/marrlab/genbloom) (confidence: medium) * **[Attenuation-Resilient Alternating Optimization for Laparoscopic Liver Landmark Detection](https://arxiv.org/abs/2605.26630v1)** - [Code](https://github.com/hyperiondk115/a2onet) (confidence: high) * **[X-Edit: Exact, Explicit, and Explainable Null-Space Editing for Medical Vision Transformers](https://arxiv.org/abs/2605.24932v1)** - [Code](https://github.com/henrylau7/x-edit) (confidence: medium) * **[ImPartial: Multi-channel Whole-Cell Segmentation using Partial Annotations](https://arxiv.org/abs/2605.24128v1)** - [Code](https://github.com/nadeemlab/impartial) (confidence: medium) * **[VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering](https://arxiv.org/abs/2605.20772v2)** - [Code](https://github.com/jiayi-chen-au/vihd) (confidence: high) * **[Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings](https://arxiv.org/abs/2605.19374v1)** - [Code](https://github.com/dopaminelcy/conns) (confidence: high) * **[BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability](https://arxiv.org/abs/2605.13059v1)** - [Code](https://github.com/sdh-lab/brainanytime) (confidence: medium) * **[Contrastive Learning under Noisy Temporal Self-Supervision for Colonoscopy Videos](https://arxiv.org/abs/2605.12320v2)** - [Code](https://github.com/lparolari/ntssl) (confidence: medium) * **[Wasserstein-Aligned Localisation for VLM-Based Distributional OOD Detection in Medical Imaging](https://arxiv.org/abs/2605.05161v2)** - [Code](https://github.com/bkainz/waldo_miccai26_demo) (confidence: high) * **[Exemplar Diffusion: Improving Medical Object Detection with Opportunistic Labels](https://arxiv.org/abs/2603.15267v1)** - [Code](https://github.com/waahlstrand/exemplardiffusion) (confidence: high) * **[Evidential Perfusion Physics-Informed Neural Networks with Residual Uncertainty Quantification](https://arxiv.org/abs/2603.09359v2)** - [Code](https://github.com/jhlee0619/eppinn) (confidence: medium) * **[Echo2ECG: Enhancing ECG Representations with Cardiac Morphology from Multi-View Echos](https://arxiv.org/abs/2603.08505v2)** - [Code](https://github.com/michelleespranita/echo2ecg) (confidence: medium) * **[Benchmark-Ready 3D Anatomical Shape Classification](https://arxiv.org/abs/2511.01613v1)** - [Code](https://github.com/tomaskrsicka/medshapenet19-pspooling) (confidence: high) * **[MeisenMeister: A Simple Two Stage Pipeline for Breast Cancer Classification on MRI](https://arxiv.org/abs/2510.27326v1)** - [Code](https://github.com/mic-dkfz/meisenmeister) (confidence: high) * **[Adaptive Stain Normalization for Cross-Domain Medical Histology](https://arxiv.org/abs/2510.06592v1)** - [Code](https://github.com/xutianyue/beerlanet) (confidence: high) * **[SpurBreast: A Curated Dataset for Investigating Spurious Correlations in Real-world Breast MRI Classification](https://arxiv.org/abs/2510.02109v1)** - [Code](https://github.com/utkuozbulak/spurbreast) (confidence: high) * **[High-Order Progressive Trajectory Matching for Medical Image Dataset Distillation](https://arxiv.org/abs/2509.24177v1)** - [Code](https://github.com/bian-jh/hop-tm) (confidence: medium) * **[Anomaly Detection by Clustering DINO Embeddings using a Dirichlet Process Mixture](https://arxiv.org/abs/2509.19997v1)** - [Code](https://github.com/nicoschulthess/anomalydino-dpmm) (confidence: high) * **[Learning Contrastive Multimodal Fusion with Improved Modality Dropout for Disease Detection and Prediction](https://arxiv.org/abs/2509.18284v1)** - [Code](https://github.com/omron-sinicx/medical-modality-dropout) (confidence: high) * **[SLaM-DiMM: Shared Latent Modeling for Diffusion Based Missing Modality Synthesis in MRI](https://arxiv.org/abs/2509.16019v1)** - [Code](https://github.com/bheeshmsharma/slam-dimm-miccai-brats-challenge-2025) (confidence: medium) * **[The Missing Piece: A Case for Pre-Training in 3D Medical Object Detection](https://arxiv.org/abs/2509.15947v1)** - [Code](https://github.com/mic-dkfz/nndetection-finetuning) (confidence: high) * **[Robust Fetal Pose Estimation across Gestational Ages via Cross-Population Augmentation](https://arxiv.org/abs/2509.12062v1)** - [Code](https://github.com/sebodiaz/cross-population-pose) (confidence: medium) * **[Invisible Attributes, Visible Biases: Exploring Demographic Shortcuts in MRI-based Alzheimer's Disease Classification](https://arxiv.org/abs/2509.09558v1)** - [Code](https://github.com/acharaakshit/shortmr) (confidence: high) * **[Modality-Agnostic Input Channels Enable Segmentation of Brain lesions in Multimodal MRI with Sequences Unavailable During Training](https://arxiv.org/abs/2509.09290v1)** - [Code](https://github.com/anthony-p-addison/agn-mod-seg) (confidence: medium) * **[SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training](https://arxiv.org/abs/2509.08311v1)** - [Code](https://github.com/tonichopp/simcrop) (confidence: medium) * **[XOCT: Enhancing OCT to OCTA Translation via Cross-Dimensional Supervised Multi-Scale Feature Learning](https://arxiv.org/abs/2509.07455v1)** - [Code](https://github.com/uci-cbcl/xoct) (confidence: medium) * **[Leveraging Generic Foundation Models for Multimodal Surgical Data Analysis](https://arxiv.org/abs/2509.06831v1)** - [Code](https://github.com/digitalsurgerylab-basel/ml-cds-2025) (confidence: medium) * **[PRECISE-AS: Personalized Reinforcement Learning for Efficient Point-of-Care Echocardiography in Aortic Stenosis Diagnosis](https://arxiv.org/abs/2509.02898v1)** - [Code](https://github.com/armin-saadat/precise-as) (confidence: high) * **[Ontology-Based Concept Distillation for Radiology Report Retrieval and Labeling](https://arxiv.org/abs/2508.19915v1)** - [Code](https://github.com/felix-012/ontology-concept-distillation) (confidence: high) * **[OccluNet: Spatio-Temporal Deep Learning for Occlusion Detection on DSA](https://arxiv.org/abs/2508.14286v1)** - [Code](https://github.com/anushka-kore/occlunet) (confidence: high) * **[MOC: Meta-Optimized Classifier for Few-Shot Whole Slide Image Classification](https://arxiv.org/abs/2508.09967v1)** - [Code](https://github.com/xmed-lab/moc) (confidence: high) * **[REFLECT: Rectified Flows for Efficient Brain Anomaly Correction Transport](https://arxiv.org/abs/2508.02889v1)** - [Code](https://github.com/farzad-bz/reflect) (confidence: medium) * **[Large Kernel MedNeXt for Breast Tumor Segmentation and Self-Normalizing Network for pCR Classification in Magnetic Resonance Images](https://arxiv.org/abs/2508.01831v1)** - [Code](https://github.com/toufiqmusah/caladan-mama-mia) (confidence: high) * **[CLIMD: A Curriculum Learning Framework for Imbalanced Multimodal Diagnosis](https://arxiv.org/abs/2508.01594v1)** - [Code](https://github.com/khan-ujs/climd) (confidence: medium) * **[Diffusion-Based User-Guided Data Augmentation for Coronary Stenosis Detection](https://arxiv.org/abs/2508.00438v1)** - [Code](https://github.com/medipixel/digda) (confidence: high) * **[$MV_{Hybrid}$: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Models](https://arxiv.org/abs/2508.00383v1)** - [Code](https://github.com/deepnoid-ai/mvhybrid) (confidence: medium) * **[GEPAR3D: Geometry Prior-Assisted Learning for 3D Tooth Segmentation](https://arxiv.org/abs/2508.00155v1)** - [Code](https://github.com/tomek1911/gepar3d) (confidence: medium) * **[Advancing Fetal Ultrasound Image Quality Assessment in Low-Resource Settings](https://arxiv.org/abs/2507.22802v1)** - [Code](https://github.com/donglihe-hub/fetalclip-iqa) (confidence: medium) * **[Predict Patient Self-reported Race from Skin Histological Images](https://arxiv.org/abs/2507.21912v2)** - [Code](https://github.com/sinai-computational-pathology/cpath_saif) (confidence: high) * **[VidFuncta: Towards Generalizable Neural Representations for Ultrasound Videos](https://arxiv.org/abs/2507.21863v1)** - [Code](https://github.com/juliawolleb/vidfuncta_public) (confidence: high) * **[Fairness and Robustness of CLIP-Based Models for Chest X-rays](https://arxiv.org/abs/2507.21291v1)** - [Code](https://github.com/theosourget/clip_cxr_fairness) (confidence: medium) * **[VAMPIRE: Uncovering Vessel Directional and Morphological Information from OCTA Images for Cardiovascular Disease Risk Factor Prediction](https://arxiv.org/abs/2507.20017v1)** - [Code](https://github.com/xmed-lab/vampire) (confidence: high) * **[RegScore: Scoring Systems for Regression Tasks](https://arxiv.org/abs/2507.19155v1)** - [Code](https://github.com/sanoscience/regscore) (confidence: medium) * **[Towards Holistic Surgical Scene Graph](https://arxiv.org/abs/2507.15541v2)** - [Code](https://github.com/ailab-kyunghee/ssg-com) (confidence: medium) * **[SurgX: Neuron-Concept Association for Explainable Surgical Phase Recognition](https://arxiv.org/abs/2507.15418v1)** - [Code](https://github.com/ailab-kyunghee/surgx) (confidence: high) * **[Focus on Texture: Rethinking Pre-training in Masked Autoencoders for Medical Image Classification](https://arxiv.org/abs/2507.10869v1)** - [Code](https://github.com/chetanmadan/glcm-mae) (confidence: high) * **[BenchReAD: A systematic benchmark for retinal anomaly detection](https://arxiv.org/abs/2507.10492v1)** - [Code](https://github.com/dopaminelcy/benchread) (confidence: high) * **[Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport](https://arxiv.org/abs/2507.04999v1)** - [Code](https://github.com/qinkaiyu/rima) (confidence: medium) * **[Parameterized Diffusion Optimization enabled Autoregressive Ordinal Regression for Diabetic Retinopathy Grading](https://arxiv.org/abs/2507.04978v1)** - [Code](https://github.com/qinkaiyu/aor-dr) (confidence: medium) * **[Geometric-Guided Few-Shot Dental Landmark Detection with Human-Centric Foundation Model](https://arxiv.org/abs/2507.04710v1)** - [Code](https://github.com/xmed-lab/geosapiens) (confidence: high) * **[T-SYNTH: A Knowledge-Based Dataset of Synthetic Breast Images](https://arxiv.org/abs/2507.04038v2)** - [Code](https://github.com/didsr/tsynth-release) (confidence: medium) * **[MvHo-IB: Multi-View Higher-Order Information Bottleneck for Brain Disorder Diagnosis](https://arxiv.org/abs/2507.02847v1)** - [Code](https://github.com/zky04/mvho-ib) (confidence: medium) * **[Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound](https://arxiv.org/abs/2507.01401v1)** - [Code](https://github.com/ll-ac/aacls) (confidence: high) * **[Text-Guided Multi-Instance Learning for Scoliosis Screening via Gait Video Analysis](https://arxiv.org/abs/2507.02996v1)** - [Code](https://github.com/lhqqq/tg-milnet) (confidence: medium) * **[Topology-Constrained Learning for Efficient Laparoscopic Liver Landmark Detection](https://arxiv.org/abs/2507.00519v1)** - [Code](https://github.com/cuiruize/toponet) (confidence: high) * **[MadCLIP: Few-shot Medical Anomaly Detection with CLIP](https://arxiv.org/abs/2506.23810v1)** - [Code](https://github.com/mahshid1998/madclip) (confidence: high) * **[MReg: A Novel Regression Model with MoE-based Video Feature Mining for Mitral Regurgitation Diagnosis](https://arxiv.org/abs/2506.23648v1)** - [Code](https://github.com/cskdstz/mreg) (confidence: high) * **[Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound](https://arxiv.org/abs/2506.23538v2)** - [Code](https://github.com/yuhoo0302/cua-us) (confidence: high) * **[Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification](https://arxiv.org/abs/2506.23298v3)** - [Code](https://github.com/xingbpshen/medical-calibration-fairness-mllm) (confidence: high) * **[BrainMT: A Hybrid Mamba-Transformer Architecture for Modeling Long-Range Dependencies in Functional MRI Data](https://arxiv.org/abs/2506.22591v1)** - [Code](https://github.com/arunkumar-kannan/brainmt-fmri) (confidence: medium) * **[Cardiovascular disease classification using radiomics and geometric features from cardiac CT](https://arxiv.org/abs/2506.22226v2)** - [Code](https://github.com/biomedia-mira/grc-net) (confidence: high) * **[RetFiner: A Vision-Language Refinement Scheme for Retinal Foundation Models](https://arxiv.org/abs/2506.22149v1)** - [Code](https://github.com/ronnief1/retfiner) (confidence: medium) * **[Tied Prototype Model for Few-Shot Medical Image Segmentation](https://arxiv.org/abs/2506.22101v1)** - [Code](https://github.com/hjk92g/tpm-fss) (confidence: medium) * **[Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement](https://arxiv.org/abs/2506.20254v2)** - [Code](https://github.com/camma-public/spa) (confidence: medium) * **[Assessing Risk of Stealing Proprietary Models for Medical Imaging Tasks](https://arxiv.org/abs/2506.19464v1)** - [Code](https://github.com/rajankita/querywise) (confidence: medium) * **[Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction](https://arxiv.org/abs/2506.19363v1)** - [Code](https://github.com/sot176/longitudinal_mammogram_alignment) (confidence: medium) * **[Targeted False Positive Synthesis via Detector-guided Adversarial Diffusion Attacker for Robust Polyp Detection](https://arxiv.org/abs/2506.18134v1)** - [Code](https://github.com/huster-hq/dada) (confidence: high) * **[Training-free Test-time Improvement for Explainable Medical Image Classification](https://arxiv.org/abs/2506.18070v1)** - [Code](https://github.com/riverback/tf-tti-xmed) (confidence: high) * **[Trustworthy Few-Shot Transfer of Medical VLMs through Split Conformal Prediction](https://arxiv.org/abs/2506.17503v1)** - [Code](https://github.com/jusiro/sca-t) (confidence: medium) * **[VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction](https://arxiv.org/abs/2506.17412v1)** - [Code](https://github.com/mortal-suen/vmra-mar) (confidence: medium) * **[OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models](https://arxiv.org/abs/2506.15318v3)** - [Code](https://github.com/hilab-git/openpath) (confidence: high) * **[DSSAU-Net:U-Shaped Hybrid Network for Pubic Symphysis and Fetal Head Segmentation](https://arxiv.org/abs/2506.03684v1)** - [Code](https://github.com/xiazunhui/dssau-net) (confidence: high) * **[Holistic White-light Polyp Classification via Alignment-free Dense Distillation of Auxiliary Optical Chromoendoscopy](https://arxiv.org/abs/2505.19319v3)** - [Code](https://github.com/huster-hq/add) (confidence: high) * **[CENet: Context Enhancement Network for Medical Image Segmentation](https://arxiv.org/abs/2505.18423v1)** - [Code](https://github.com/xmindflow/cenet) (confidence: medium) * **[Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays](https://arxiv.org/abs/2505.17311v1)** - [Code](https://github.com/nth221/diff3m) (confidence: high) * **[Learning Concept-Driven Logical Rules for Interpretable and Generalizable Medical Image Classification](https://arxiv.org/abs/2505.14049v2)** - [Code](https://github.com/obiyoag/crl) (confidence: high) * **[Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models](https://arxiv.org/abs/2505.09858v1)** - [Code](https://gitlab.com/nct_tso_public/surgvgen) (confidence: medium) * **[BrainNetMLP: An Efficient and Effective Baseline for Functional Brain Network Classification](https://arxiv.org/abs/2505.11538v2)** - [Code](https://github.com/jayceonho/brainnetmlp) (confidence: high) * **[ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking](https://arxiv.org/abs/2505.08581v1)** - [Code](https://github.com/jinlab-imvr/resurgsam2) (confidence: medium) * **[A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images](https://arxiv.org/abs/2504.08481v4)** - [Code](https://github.com/kdjoumessi/self-explainable-cnn-transformer) (confidence: high) * **[DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology Diagnosis](https://arxiv.org/abs/2503.17536v1)** - [Code](https://github.com/munia03/dermdiff) (confidence: medium) * **[Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models](https://arxiv.org/abs/2503.14966v1)** - [Code](https://github.com/medaitech/u_i2v) (confidence: high) * **[Are ECGs enough? Deep learning classification of pulmonary embolism using electrocardiograms](https://arxiv.org/abs/2503.08960v2)** - [Code](https://github.com/joaodsmarques/are-ecgs-enough-deep-learning-classifiers) (confidence: high) * **[Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification](https://arxiv.org/abs/2503.08384v2)** - [Code](https://github.com/ss-sun/protomil) (confidence: high) * **[Automatic detection and prediction of nAMD activity change in retinal OCT using Siamese networks and Wasserstein Distance for ordinality](https://arxiv.org/abs/2501.14323v1)** - [Code](https://github.com/emretaha/siamese-emd-for-amd-change) (confidence: high) * **[RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment](https://arxiv.org/abs/2501.07525v2)** - [Code](https://github.com/difeigu/radalign) (confidence: medium) * **[SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data](https://arxiv.org/abs/2412.16078v1)** - [Code](https://github.com/surgical-vision/segcol_challenge) (confidence: medium) * **[Automatic dataset shift identification to support safe deployment of medical imaging AI](https://arxiv.org/abs/2411.07940v3)** - [Code](https://github.com/biomedia-mira/shift_identification) (confidence: medium) * **[Automated Spinal MRI Labelling from Reports Using a Large Language Model](https://arxiv.org/abs/2410.17235v1)** - [Code](https://github.com/robinyjpark/autolabelclassifier) (confidence: medium) * **[Ensemble of ConvNeXt V2 and MaxViT for Long-Tailed CXR Classification with View-Based Aggregation](https://arxiv.org/abs/2410.10710v2)** - [Code](https://github.com/yamagishi0824/cxrlt24-multiview-pp) (confidence: high) * **[FACMIC: Federated Adaptative CLIP Model for Medical Image Classification](https://arxiv.org/abs/2410.14707v1)** - [Code](https://github.com/aipmlab/facmic) (confidence: high) * **[Optimising for the Unknown: Domain Alignment for Cephalometric Landmark Detection](https://arxiv.org/abs/2410.04445v1)** - [Code](https://github.com/julian-wyatt/optimisingfortheunknown) (confidence: high) * **[Hard Negative Sample Mining for Whole Slide Image Classification](https://arxiv.org/abs/2410.02212v1)** - [Code](https://github.com/winston52/hnm-wsi) (confidence: high) * **[TSBP: Improving Object Detection in Histology Images via Test-time Self-guided Bounding-box Propagation](https://arxiv.org/abs/2409.16678v1)** - [Code](https://github.com/jwhgdeu/tsbp) (confidence: high) * **[Intrapartum Ultrasound Image Segmentation of Pubic Symphysis and Fetal Head Using Dual Student-Teacher Framework with CNN-ViT Collaborative Learning](https://arxiv.org/abs/2409.06928v1)** - [Code](https://github.com/jjm1589/dstct) (confidence: medium) * **[PatchAlign:Fair and Accurate Skin Disease Image Classification by Alignment with Clinical Labels](https://arxiv.org/abs/2409.04975v1)** - [Code](https://github.com/aayushmanace/patchalign24) (confidence: high) * **[Spatial Diffusion for Cell Layout Generation](https://arxiv.org/abs/2409.03106v1)** - [Code](https://github.com/superlc1995/diffusion-cell) (confidence: medium) * **[Evaluating Reliability in Medical DNNs: A Critical Analysis of Feature and Confidence-Based OOD Detection](https://arxiv.org/abs/2408.17337v1)** - [Code](https://github.com/harryanthony/evaluating_ood_detection) (confidence: high) * **[PromptSmooth: Certifying Robustness of Medical Vision-Language Models via Prompt Learning](https://arxiv.org/abs/2408.16769v1)** - [Code](https://github.com/nhussein/promptsmooth) (confidence: medium) * **[Tackling Data Heterogeneity in Federated Learning via Loss Decomposition](https://arxiv.org/abs/2408.12300v2)** - [Code](https://github.com/zeng-shuang/fedld) (confidence: medium) * **[BMFT: Achieving Fairness via Bias-based Weight Masking Fine-tuning](https://arxiv.org/abs/2408.06890v2)** - [Code](https://github.com/vios-s/bmft) (confidence: high) * **[CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning](https://arxiv.org/abs/2408.04949v1)** - [Code](https://github.com/gianlucarloni/crocodile) (confidence: high) * **[Lesion Elevation Prediction from Skin Images Improves Diagnosis](https://arxiv.org/abs/2408.02792v1)** - [Code](https://github.com/sfu-mial/lesionelevation) (confidence: high) * **[Robust Curve Detection in Volumetric Medical Imaging via Attraction Field](https://arxiv.org/abs/2408.01159v2)** - [Code](https://github.com/neuro-ml/curve-detection) (confidence: high) * **[MicroMIL: Graph-Based Multiple Instance Learning for Context-Aware Diagnosis with Microscopic Images](https://arxiv.org/abs/2407.21604v4)** - [Code](https://github.com/kimjongwoo-cell/micromil) (confidence: medium) * **[UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks](https://arxiv.org/abs/2408.07075v2)** - [Code](https://github.com/basiralab/unifed) (confidence: high) * **[Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations](https://arxiv.org/abs/2407.20072v1)** - [Code](https://github.com/13204942/fu-lora) (confidence: high) * **[CoMoTo: Unpaired Cross-Modal Lesion Distillation Improves Breast Lesion Detection in Tomosynthesis](https://arxiv.org/abs/2407.17620v1)** - [Code](https://github.com/muhammad-al-barbary/comoto) (confidence: high) * **[Graph Neural Networks: A suitable Alternative to MLPs in Latent 3D Medical Image Classification?](https://arxiv.org/abs/2407.17219v1)** - [Code](https://github.com/compai-lab/2024-miccai-grail-kiechle) (confidence: high) * **[ETSCL: An Evidence Theory-Based Supervised Contrastive Learning Framework for Multi-modal Glaucoma Grading](https://arxiv.org/abs/2407.14230v1)** - [Code](https://github.com/master-shix/etscl) (confidence: medium) * **[Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data](https://arxiv.org/abs/2407.12669v1)** - [Code](https://github.com/richardobi/mammo_dp) (confidence: high) * **[FD-SOS: Vision-Language Open-Set Detectors for Bone Fenestration and Dehiscence Detection from Intraoral Images](https://arxiv.org/abs/2407.09088v1)** - [Code](https://github.com/xmed-lab/fd-sos) (confidence: high) * **[SlideGCD: Slide-based Graph Collaborative Training with Knowledge Distillation for Whole Slide Image Classification](https://arxiv.org/abs/2407.08968v2)** - [Code](https://github.com/hfut-mialab/slidegcd) (confidence: high) * **[Symmetry Awareness Encoded Deep Learning Framework for Brain Imaging Analysis](https://arxiv.org/abs/2407.08948v1)** - [Code](https://github.com/bitmyron/sa-swin) (confidence: high) * **[RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features](https://arxiv.org/abs/2407.05683v2)** - [Code](https://github.com/nainye/radiomicsfill) (confidence: medium) * **[CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading with Ranking-aware Prompting](https://arxiv.org/abs/2407.04068v1)** - [Code](https://github.com/qinkaiyu/clip-dr) (confidence: medium) * **[Vision Mamba for Classification of Breast Ultrasound Images](https://arxiv.org/abs/2407.03552v2)** - [Code](https://github.com/anasiri/bu-mamba) (confidence: high) * **[An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis](https://arxiv.org/abs/2407.03018v1)** - [Code](https://github.com/xmed-lab/geca) (confidence: medium) * **[Centerline Boundary Dice Loss for Vascular Segmentation](https://arxiv.org/abs/2407.01517v1)** - [Code](https://github.com/pengchengshi1220/cbdice) (confidence: medium) * **[Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound](https://arxiv.org/abs/2407.00267v1)** - [Code](https://github.com/hawaii-ai/bus-cbm) (confidence: high) * **[BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision](https://arxiv.org/abs/2406.19148v1)** - [Code](https://github.com/kitbransby/backmix) (confidence: medium) * **[Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis](https://arxiv.org/abs/2406.19130v1)** - [Code](https://github.com/obiyoag/evi-cem) (confidence: medium) * **[FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity](https://arxiv.org/abs/2406.18995v1)** - [Code](https://github.com/szbonaldo/fedmlp) (confidence: high) * **[MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions](https://arxiv.org/abs/2406.17536v3)** - [Code](https://github.com/francescodisalvo05/medmnistc-api) (confidence: high) * **[Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases Detection](https://arxiv.org/abs/2406.17338v1)** - [Code](https://github.com/hp-ml/miccai2024) (confidence: high) * **[DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation](https://arxiv.org/abs/2406.15182v2)** - [Code](https://github.com/ayanglab/diffexplainer) (confidence: high) * **[Cephalometric Landmark Detection across Ages with Prototypical Network](https://arxiv.org/abs/2406.12577v1)** - [Code](https://github.com/shanghaitech-impact/cephalometric-landmark-detection-across-ages-with-prototypical-network) (confidence: high) * **[Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification](https://arxiv.org/abs/2406.05596v2)** - [Code](https://github.com/yhygao/explicd) (confidence: high) * **[LNQ Challenge 2023: Learning Mediastinal Lymph Node Segmentation with a Probabilistic Lymph Node Atlas](https://arxiv.org/abs/2406.03984v1)** - [Code](https://github.com/micai-imi-uzl/lnq2023) (confidence: medium) * **[EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery Videos](https://arxiv.org/abs/2405.19644v3)** - [Code](https://github.com/fujiry0/egosurgery) (confidence: high) * **[SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform Regression](https://arxiv.org/abs/2405.16813v4)** - [Code](https://github.com/oulu-imeds/singr) (confidence: medium) * **[RET-CLIP: A Retinal Image Foundation Model Pre-trained with Clinical Diagnostic Reports](https://arxiv.org/abs/2405.14137v2)** - [Code](https://github.com/sstonemason/ret-clip) (confidence: high) * **[Position-Guided Prompt Learning for Anomaly Detection in Chest X-Rays](https://arxiv.org/abs/2405.11976v2)** - [Code](https://github.com/sunzc-sunny/ppad) (confidence: high) * **[Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography](https://arxiv.org/abs/2405.12255v2)** - [Code](https://github.com/batmanlab/mammo-clip) (confidence: medium) * **[MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection](https://arxiv.org/abs/2405.11315v1)** - [Code](https://github.com/cnulab/mediclip) (confidence: high) * **[Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification](https://arxiv.org/abs/2405.19346v2)** - [Code](https://github.com/sionan/miccai2024-restl) (confidence: high) * **[MMFusion: Multi-modality Diffusion Model for Lymph Node Metastasis Diagnosis in Esophageal Cancer](https://arxiv.org/abs/2405.09539v2)** - [Code](https://github.com/wuchengyu123/mmfusion) (confidence: medium) * **[Gaze-DETR: Using Expert Gaze to Reduce False Positives in Vulvovaginal Candidiasis Screening](https://arxiv.org/abs/2405.09463v1)** - [Code](https://github.com/yankong0408/gaze-detr) (confidence: medium) * **[Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis](https://arxiv.org/abs/2405.08681v1)** - [Code](https://github.com/kqp1227/sensitive-channel-pruning) (confidence: high) * **[Longitudinal Mammogram Risk Prediction](https://arxiv.org/abs/2404.19083v1)** - [Code](https://github.com/batuhankmkaraman/lomar) (confidence: medium) * **[Language Models Meet Anomaly Detection for Better Interpretability and Generalizability](https://arxiv.org/abs/2404.07622v2)** - [Code](https://github.com/compai-lab/miccai-2024-junli) (confidence: high) * **[Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks](https://arxiv.org/abs/2403.19880v1)** - [Code](https://github.com/pooria90/diffecho) (confidence: medium) * **[Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation](https://arxiv.org/abs/2403.09942v1)** - [Code](https://github.com/yaziciz/glims) (confidence: medium) * **[Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective](https://arxiv.org/abs/2403.09303v3)** - [Code](https://github.com/caiyu6666/ae4ad) (confidence: high) * **[Shortcut Learning in Medical Image Segmentation](https://arxiv.org/abs/2403.06748v2)** - [Code](https://github.com/nina-weng/shortcut_skinseg) (confidence: medium) * **[From Pixel to Cancer: Cellular Automata in Computed Tomography](https://arxiv.org/abs/2403.06459v2)** - [Code](https://github.com/mrgiovanni/pixel2cancer) (confidence: medium) * **[Debiased Noise Editing on Foundation Models for Fair Medical Image Classification](https://arxiv.org/abs/2403.06104v4)** - [Code](https://github.com/ubc-tea/dne-foundation-model-fairness) (confidence: high) * **[[Citation needed] Data usage and citation practices in medical imaging conferences](https://arxiv.org/abs/2402.03003v2)** - [Code](https://github.com/theosourget/public_medical_datasets_references) (confidence: medium) | [Code2](https://github.com/theosourget/pdf_annotator) * **[VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification](https://arxiv.org/abs/2402.01034v3)** - [Code](https://github.com/lzl199704/vis-mae) (confidence: high) * **[Pixel-Wise Recognition for Holistic Surgical Scene Understanding](https://arxiv.org/abs/2401.11174v2)** - [Code](https://github.com/bcv-uniandes/grasp) (confidence: high) * **[Prompt-based Grouping Transformer for Nucleus Detection and Classification](https://arxiv.org/abs/2310.14176v1)** - [Code](https://github.com/lhaof/pgt) (confidence: high) * **[Visual-Attribute Prompt Learning for Progressive Mild Cognitive Impairment Prediction](https://arxiv.org/abs/2310.14158v1)** - [Code](https://github.com/lhaof/vapl) (confidence: medium) * **[CXR-CLIP: Toward Large Scale Chest X-ray Language-Image Pre-training](https://arxiv.org/abs/2310.13292v1)** - [Code](https://github.com/kakaobrain/cxr-clip) (confidence: medium) * **[Revisiting Cephalometric Landmark Detection from the view of Human Pose Estimation with Lightweight Super-Resolution Head](https://arxiv.org/abs/2309.17143v1)** - [Code](https://github.com/5k5000/cldetection2023) (confidence: high) * **[A mirror-Unet architecture for PET/CT lesion segmentation](https://arxiv.org/abs/2309.13398v1)** - [Code](https://github.com/yrotstein/autopet2023_mv1) (confidence: medium) * **[Privacy-preserving Early Detection of Epileptic Seizures in Videos](https://arxiv.org/abs/2309.08794v1)** - [Code](https://github.com/devd1092/seizure-detection) (confidence: high) * **[Performance Metrics for Probabilistic Ordinal Classifiers](https://arxiv.org/abs/2309.08701v1)** - [Code](https://github.com/agaldran/prob_ord_metrics) (confidence: medium) * **[A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos](https://arxiv.org/abs/2309.04702v1)** - [Code](https://github.com/alfredqin/stnet) (confidence: high) * **[Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening](https://arxiv.org/abs/2309.02670v1)** - [Code](https://github.com/cjdbehumble/miccai2023-vvc-screening) (confidence: high) * **[On the use of Mahalanobis distance for out-of-distribution detection with neural networks for medical imaging](https://arxiv.org/abs/2309.01488v1)** - [Code](https://github.com/harryanthony/mahalanobis-ood-detection) (confidence: high) * **[Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection](https://arxiv.org/abs/2309.00108v1)** - [Code](https://github.com/mindflow-institue/laplacian-former) (confidence: high) * **[Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment](https://arxiv.org/abs/2308.16735v1)** - [Code](https://github.com/felixwag/staralign) (confidence: high) * **[A Sequential Framework for Detection and Classification of Abnormal Teeth in Panoramic X-rays](https://arxiv.org/abs/2309.00027v2)** - [Code](https://github.com/tudordascalu/2d-teeth-detection-challenge) (confidence: high) * **[CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention](https://arxiv.org/abs/2308.16145v2)** - [Code](https://github.com/zhanghx-iim-ahu/circleformer) (confidence: high) * **[Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data](https://arxiv.org/abs/2308.15881v1)** - [Code](https://github.com/nki-radiology/interpretability_augmentation) (confidence: medium) * **[DETDet: Dual Ensemble Teeth Detection](https://arxiv.org/abs/2308.14070v1)** - [Code](https://github.com/bestever-choi/evident) (confidence: high) * **[Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers](https://arxiv.org/abs/2308.13442v2)** - [Code](https://github.com/mindflow-institue/waveformer) (confidence: medium) * **[Unsupervised Domain Adaptation for Anatomical Landmark Detection](https://arxiv.org/abs/2308.13286v1)** - [Code](https://github.com/jhb86253817/uda_med_landmark) (confidence: high) * **[Revisiting Skin Tone Fairness in Dermatological Lesion Classification](https://arxiv.org/abs/2308.09640v1)** - [Code](https://github.com/tkalbl/revisitingskintonefairness) (confidence: high) * **[Decoupled conditional contrastive learning with variable metadata for prostate lesion detection](https://arxiv.org/abs/2308.09542v1)** - [Code](https://github.com/camilleruppli/decoupled_ccl) (confidence: high) * **[Inferior Alveolar Nerve Segmentation in CBCT images using Connectivity-Based Selective Re-training](https://arxiv.org/abs/2308.09298v1)** - [Code](https://github.com/garynico517/ssl-ian-retraining) (confidence: medium) * **[How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?](https://arxiv.org/abs/2308.09180v1)** - [Code](https://github.com/vita-group/prunecxr) (confidence: high) * **[SEDA: Self-Ensembling ViT with Defensive Distillation and Adversarial Training for robust Chest X-rays Classification](https://arxiv.org/abs/2308.07874v1)** - [Code](https://github.com/razaimam45/seda) (confidence: high) * **[Synthetic Augmentation with Large-scale Unconditional Pre-training](https://arxiv.org/abs/2308.04020v1)** - [Code](https://github.com/karenyyy/histodiffaug) (confidence: high) * **[DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation](https://arxiv.org/abs/2308.02959v1)** - [Code](https://github.com/mindflow-institue/dermosegdiff) (confidence: medium) * **[Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection](https://arxiv.org/abs/2308.01639v1)** - [Code](https://github.com/mediabrain-sjtu/ecgad) (confidence: high) * **[Fundus-Enhanced Disease-Aware Distillation Model for Retinal Disease Classification from OCT Images](https://arxiv.org/abs/2308.00291v1)** - [Code](https://github.com/xmed-lab/fddm) (confidence: high) * **[Cross-Dataset Adaptation for Instrument Classification in Cataract Surgery Videos](https://arxiv.org/abs/2308.04035v1)** - [Code](https://github.com/jayparanjape/barlow-adaptor) (confidence: high) * **[L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space](https://arxiv.org/abs/2307.16459v2)** - [Code](https://github.com/csiro-robotics/l3dmc) (confidence: medium) * **[Understanding Silent Failures in Medical Image Classification](https://arxiv.org/abs/2307.14729v2)** - [Code](https://github.com/iml-dkfz/sf-visuals) (confidence: high) * **[ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography](https://arxiv.org/abs/2307.14433v1)** - [Code](https://github.com/hooman007/protoasnet) (confidence: high) * **[Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging](https://arxiv.org/abs/2307.12542v2)** - [Code](https://github.com/med-air/client-dp-fl) (confidence: medium) * **[GLSFormer: Gated - Long, Short Sequence Transformer for Step Recognition in Surgical Videos](https://arxiv.org/abs/2307.11081v1)** - [Code](https://github.com/nisargshah1999/glsformer) (confidence: high) * **[Surgical Action Triplet Detection by Mixed Supervised Learning of Instrument-Tissue Interactions](https://arxiv.org/abs/2307.09548v1)** - [Code](https://github.com/camma-public/mcit-ig) (confidence: high) * **[Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network](https://arxiv.org/abs/2307.08268v2)** - [Code](https://github.com/alibaba-damo-academy/pixel-lesion-patient-network) (confidence: high) * **[MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis](https://arxiv.org/abs/2307.07807v1)** - [Code](https://github.com/jeunyuli/muaf) (confidence: high) * **[Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training](https://arxiv.org/abs/2307.07246v2)** - [Code](https://github.com/chenxiaofei-cs/kobo) (confidence: high) * **[CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery](https://arxiv.org/abs/2307.05182v3)** - [Code](https://github.com/longbai1006/cat-vil) (confidence: high) * **[Weakly-supervised positional contrastive learning: application to cirrhosis classification](https://arxiv.org/abs/2307.04617v3)** - [Code](https://github.com/guerbet-ai/wsp-contrastive) (confidence: high) * **[Unsupervised 3D out-of-distribution detection with latent diffusion models](https://arxiv.org/abs/2307.03777v1)** - [Code](https://github.com/marksgraham/ddpm-ood) (confidence: high) * **[Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery](https://arxiv.org/abs/2307.03662v1)** - [Code](https://github.com/br0202/sensing_area_detection) (confidence: medium) * **[The Role of Subgroup Separability in Group-Fair Medical Image Classification](https://arxiv.org/abs/2307.02791v1)** - [Code](https://github.com/biomedia-mira/subgroup-separability) (confidence: high) * **[Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks](https://arxiv.org/abs/2307.00899v1)** - [Code](https://github.com/matt-baugh/many-tasks-make-light-work) (confidence: medium) * **[Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism](https://arxiv.org/abs/2307.00895v1)** - [Code](https://github.com/netherlands-cancer-institute/ce-mri) (confidence: medium) * **[Beyond the Snapshot: Brain Tokenized Graph Transformer for Longitudinal Brain Functional Connectome Embedding](https://arxiv.org/abs/2307.00858v2)** - [Code](https://github.com/zijiand/brain-tokengt) (confidence: high) * **[Zero-shot Nuclei Detection via Visual-Language Pre-trained Models](https://arxiv.org/abs/2306.17659v1)** - [Code](https://github.com/wuyongjiancode/vlpmnud) (confidence: high) * **[Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train](https://arxiv.org/abs/2306.16741v4)** - [Code](https://github.com/med-air/endo-fm) (confidence: high) * **[Cross-Validation Is All You Need: A Statistical Approach To Label Noise Estimation](https://arxiv.org/abs/2306.13990v2)** - [Code](https://github.com/gjiananchen/recov) (confidence: medium) * **[UOD: Universal One-shot Detection of Anatomical Landmarks](https://arxiv.org/abs/2306.07615v5)** - [Code](https://github.com/heqin-zhu/uod_universal_oneshot_detection) (confidence: high) * **[Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset](https://arxiv.org/abs/2306.07089v2)** - [Code](https://github.com/m3dv/pulmonary-tree-repairing) (confidence: medium) * **[Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model](https://arxiv.org/abs/2305.19867v2)** - [Code](https://github.com/hasan1292/mddpm) (confidence: high) * **[DENTEX: Dental Enumeration and Tooth Pathosis Detection Benchmark for Panoramic X-ray](https://arxiv.org/abs/2305.19112v2)** - [Code](https://github.com/ibrahimethemhamamci/dentex) (confidence: high) * **[Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion Detection](https://arxiv.org/abs/2305.18060v2)** - [Code](https://github.com/haojunyu1998/ultradet) (confidence: high) * **[Distilling BlackBox to Interpretable models for Efficient Transfer Learning](https://arxiv.org/abs/2305.17303v7)** - [Code](https://github.com/batmanlab/miccai-2023-route-interpret-repeat-cxrs) (confidence: high) * **[Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery](https://arxiv.org/abs/2305.11692v1)** - [Code](https://github.com/longbai1006/surgical-vqla) (confidence: medium) * **[Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification](https://arxiv.org/abs/2304.02836v5)** - [Code](https://github.com/masilab/lmsignatures) (confidence: high) * **[Cross-modulated Few-shot Image Generation for Colorectal Tissue Classification](https://arxiv.org/abs/2304.01992v2)** - [Code](https://github.com/virobo-15/xm-gan) (confidence: high) * **[EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition](https://arxiv.org/abs/2304.01508v3)** - [Code](https://github.com/siyuanyan1/epvt) (confidence: high) * **[Prompt-MIL: Boosting Multi-Instance Learning Schemes via Task-specific Prompt Tuning](https://arxiv.org/abs/2303.12214v2)** - [Code](https://github.com/cvlab-stonybrook/promptmil) (confidence: medium) * **[Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays](https://arxiv.org/abs/2303.06500v3)** - [Code](https://github.com/ibrahimethemhamamci/hierarchicaldet) (confidence: high) * **[TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation](https://arxiv.org/abs/2301.06624v1)** - [Code](https://github.com/melinphd/taal) (confidence: medium) * **[Towards Holistic Surgical Scene Understanding](https://arxiv.org/abs/2212.04582v4)** - [Code](https://github.com/bcv-uniandes/tapir) (confidence: high) * **[MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis](https://arxiv.org/abs/2211.05862v4)** - [Code](https://gitlab.com/mgadermayr/mixupmil) (confidence: medium) * **[CircleSnake: Instance Segmentation with Circle Representation](https://arxiv.org/abs/2211.01254v1)** - [Code](https://github.com/hrlblab/circlesnake) (confidence: medium) * **[Rapid and robust endoscopic content area estimation: A lean GPU-based pipeline and curated benchmark dataset](https://arxiv.org/abs/2210.14771v1)** - [Code](https://github.com/charliebudd/torch-content-area) (confidence: medium) * **[Adaptive Contrastive Learning with Dynamic Correlation for Multi-Phase Organ Segmentation](https://arxiv.org/abs/2210.08652v1)** - [Code](https://github.com/masilab/dcc_cl) (confidence: medium) * **[Motion-related Artefact Classification Using Patch-based Ensemble and Transfer Learning in Cardiac MRI](https://arxiv.org/abs/2210.07717v1)** - [Code](https://github.com/ruizhe-l/cmrxmotion) (confidence: high) * **[Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks](https://arxiv.org/abs/2209.15287v1)** - [Code](https://github.com/rakshith2597/quantised-self-attentive-deep-neural-network) (confidence: medium) * **[SynthA1c: Towards Clinically Interpretable Patient Representations for Diabetes Risk Stratification](https://arxiv.org/abs/2209.10043v2)** - [Code](https://github.com/allisonjchae/dmt2riskassessment) (confidence: medium) * **[Automatic Tumor Segmentation via False Positive Reduction Network for Whole-Body Multi-Modal PET/CT Images](https://arxiv.org/abs/2209.07705v1)** - [Code](https://github.com/yigepeng/autopet_false_positive_reduction) (confidence: medium) * **[Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://arxiv.org/abs/2209.06861v1)** - [Code](https://github.com/davecasp/flowssm) (confidence: medium) * **[Morphology-preserving Autoregressive 3D Generative Modelling of the Brain](https://arxiv.org/abs/2209.03177v1)** - [Code](https://github.com/amigolab/synthanatomy) (confidence: medium) * **[HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease](https://arxiv.org/abs/2209.01822v1)** - [Code](https://github.com/mahfuzmohammad/healthygan) (confidence: medium) * **[Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study](https://arxiv.org/abs/2208.13365v1)** - [Code](https://github.com/vita-group/longtailcxr) (confidence: high) * **[SFusion: Self-attention based N-to-One Multimodal Fusion Block](https://arxiv.org/abs/2208.12776v2)** - [Code](https://github.com/scut-cszcl/sfusion) (confidence: medium) * **[Tracking by weakly-supervised learning and graph optimization for whole-embryo C. elegans lineages](https://arxiv.org/abs/2208.11467v1)** - [Code](https://github.com/funkelab/linajea) (confidence: medium) * **[Unsupervised Anomaly Localization with Structural Feature-Autoencoders](https://arxiv.org/abs/2208.10992v1)** - [Code](https://github.com/felime/feature-autoencoder) (confidence: medium) * **[A semi-supervised Teacher-Student framework for surgical tool detection and localization](https://arxiv.org/abs/2208.09926v1)** - [Code](https://github.com/mansoor-at/semi-supervised-surgical-tool-det) (confidence: high) * **[CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays](https://arxiv.org/abs/2208.03873v2)** - [Code](https://github.com/plan-lab/chexrelnet) (confidence: medium) * **[Weakly Supervised Online Action Detection for Infant General Movements](https://arxiv.org/abs/2208.03648v1)** - [Code](https://github.com/scofiedluo/wo-gma) (confidence: high) * **[Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images](https://arxiv.org/abs/2208.03327v1)** - [Code](https://github.com/marwankefah/sissi) (confidence: high) * **[LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection](https://arxiv.org/abs/2208.02122v1)** - [Code](https://github.com/ruixxxx/lssanet) (confidence: high) * **[Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis](https://arxiv.org/abs/2208.01843v1)** - [Code](https://github.com/endiqq/multi-feature-vit) (confidence: medium) * **[Deep Laparoscopic Stereo Matching with Transformers](https://arxiv.org/abs/2207.12152v1)** - [Code](https://github.com/xueliancheng/hybridstereonet-main) (confidence: high) * **[Gigapixel Whole-Slide Images Classification using Locally Supervised Learning](https://arxiv.org/abs/2207.08267v2)** - [Code](https://github.com/cvlab-stonybrook/local_learning_wsi) (confidence: high) * **[ReMix: A General and Efficient Framework for Multiple Instance Learning based Whole Slide Image Classification](https://arxiv.org/abs/2207.01805v1)** - [Code](https://github.com/jiawei-yang/remix) (confidence: high) | [Code2](https://github.com/tencentailabhealthcare/remix) * **[FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification](https://arxiv.org/abs/2207.01287v1)** - [Code](https://github.com/soleilssss/ffcnet) (confidence: high) * **[Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach](https://arxiv.org/abs/2207.00844v1)** - [Code](https://github.com/winstonhutiger/2d_vae_uda_for_3d_sythesis) (confidence: high) * **[Less is More: Adaptive Curriculum Learning for Thyroid Nodule Diagnosis](https://arxiv.org/abs/2207.00807v1)** - [Code](https://github.com/chenghui-666/acl) (confidence: high) * **[Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance](https://arxiv.org/abs/2207.00251v1)** - [Code](https://github.com/gangmingzhao/tb-attribute-weak-localization) (confidence: high) * **[CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy](https://arxiv.org/abs/2206.14951v1)** - [Code](https://github.com/nadeemlab/cep) (confidence: medium) * **[CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Radiomics and malignancy prediction](https://arxiv.org/abs/2206.14903v1)** - [Code](https://github.com/nadeemlab/cir) (confidence: medium) * **[BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes](https://arxiv.org/abs/2206.14678v1)** - [Code](https://github.com/netanellavisdris/fetalbiometry) (confidence: medium) * **[vMFNet: Compositionality Meets Domain-generalised Segmentation](https://arxiv.org/abs/2206.14538v1)** - [Code](https://github.com/vios-s/vmfnet) (confidence: medium) * **[FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification](https://arxiv.org/abs/2206.13803v3)** - [Code](https://github.com/wnn2000/fediic) (confidence: high) * **[Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classification](https://arxiv.org/abs/2206.13156v1)** - [Code](https://github.com/zhengyushan/kat) (confidence: high) * **[Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis](https://arxiv.org/abs/2206.13115v1)** - [Code](https://github.com/junl21/lacl) (confidence: medium) * **[Dynamic Bank Learning for Semi-supervised Federated Image Diagnosis with Class Imbalance](https://arxiv.org/abs/2206.13079v1)** - [Code](https://github.com/med-air/imfedsemi) (confidence: high) * **[Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays](https://arxiv.org/abs/2206.12704v1)** - [Code](https://github.com/batmanlab/agxnet) (confidence: high) * **[Surgical-VQA: Visual Question Answering in Surgical Scenes using Transformer](https://arxiv.org/abs/2206.11053v2)** - [Code](https://github.com/lalithjets/surgical_vqa) (confidence: high) * **[Test Time Transform Prediction for Open Set Histopathological Image Recognition](https://arxiv.org/abs/2206.10033v2)** - [Code](https://github.com/agaldran/t3po) (confidence: high) * **[Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays](https://arxiv.org/abs/2206.03935v3)** - [Code](https://github.com/caiyu6666/ddad) (confidence: high) * **[Free Lunch for Surgical Video Understanding by Distilling Self-Supervisions](https://arxiv.org/abs/2205.09292v2)** - [Code](https://github.com/xmed-lab/distillingself) (confidence: medium) * **[Pseudo Bias-Balanced Learning for Debiased Chest X-ray Classification](https://arxiv.org/abs/2203.09860v2)** - [Code](https://github.com/llyxc/pbbl) (confidence: high) * **[Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding](https://arxiv.org/abs/2201.11957v1)** - [Code](https://github.com/lalithjets/global-reasoned-multi-task-model) (confidence: medium) * **[Point detection through multi-instance deep heatmap regression for sutures in endoscopy](https://arxiv.org/abs/2111.08468v1)** - [Code](https://github.com/cardio-ai/suture-detection-pytorch) (confidence: high) * **[A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis](https://arxiv.org/abs/2111.06398v1)** - [Code](https://github.com/karenyyy/miccai2021attributegan) (confidence: medium) * **[Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture Classification](https://arxiv.org/abs/2110.10383v1)** - [Code](https://github.com/ljaiverson/multiview-curriculum) (confidence: high) * **[BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation](https://arxiv.org/abs/2109.12271v2)** - [Code](https://github.com/justatinydot/bitr-unet) (confidence: medium) * **[Balanced-MixUp for Highly Imbalanced Medical Image Classification](https://arxiv.org/abs/2109.09850v1)** - [Code](https://github.com/agaldran/balanced_mixup) (confidence: high) * **[Asymmetric 3D Context Fusion for Universal Lesion Detection](https://arxiv.org/abs/2109.08684v1)** - [Code](https://github.com/m3dv/alignshift) (confidence: high) * **[Automatic Polyp Segmentation via Multi-scale Subtraction Network](https://arxiv.org/abs/2108.05082v1)** - [Code](https://github.com/xiaoqi-zhao-dlut/msnet) (confidence: medium) * **[MixLacune: Segmentation of lacunes of presumed vascular origin](https://arxiv.org/abs/2108.02483v1)** - [Code](https://github.com/hjkuijf/mixlacune) (confidence: medium) * **[Adversarial learning of cancer tissue representations](https://arxiv.org/abs/2108.02223v1)** - [Code](https://github.com/adalbertocq/adversarial-learning-of-cancer-tissue-representations) (confidence: high) * **[MixMicrobleedNet: segmentation of cerebral microbleeds using nnU-Net](https://arxiv.org/abs/2108.01389v1)** - [Code](https://github.com/hjkuijf/mixmicrobleednet) (confidence: medium) * **[Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations](https://arxiv.org/abs/2107.12357v1)** - [Code](https://github.com/sophiajw/histaugan) (confidence: medium) * **[Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation](https://arxiv.org/abs/2107.06941v2)** - [Code](https://github.com/cardio-ai/detcyclegan_pytorch) (confidence: high) * **[SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance](https://arxiv.org/abs/2107.06397v1)** - [Code](https://github.com/doughtmw/surgeon-assist-net) (confidence: medium) * **[Detecting Outliers with Poisson Image Interpolation](https://arxiv.org/abs/2107.02622v1)** - [Code](https://github.com/jemtan/pii) (confidence: medium) * **[Controllable cardiac synthesis via disentangled anatomy arithmetic](https://arxiv.org/abs/2107.01748v1)** - [Code](https://github.com/vios-s/daa-gan) (confidence: medium) * **[Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation](https://arxiv.org/abs/2107.00977v1)** - [Code](https://github.com/hreynaud/uvt) (confidence: high) * **[FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos](https://arxiv.org/abs/2106.12522v2)** - [Code](https://github.com/nadeemlab/cep) (confidence: high) * **[Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching](https://arxiv.org/abs/2106.08600v1)** - [Code](https://github.com/liuquande/fedirm) (confidence: high) * **[nnDetection: A Self-configuring Method for Medical Object Detection](https://arxiv.org/abs/2106.00817v2)** - [Code](https://github.com/mic-dkfz/nndetection) (confidence: high) * **[About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations](https://arxiv.org/abs/2105.14117v4)** - [Code](https://github.com/dmitriishubin/variance-aware-training) (confidence: high) * **[You Only Learn Once: Universal Anatomical Landmark Detection](https://arxiv.org/abs/2103.04657v3)** - [Code](https://github.com/miracle-center/yolo_universal_anatomical_landmark_detection) (confidence: high) * **[NVUM: Non-Volatile Unbiased Memory for Robust Medical Image Classification](https://arxiv.org/abs/2103.04053v6)** - [Code](https://github.com/fbladl/nvum) (confidence: high) * **[Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images](https://arxiv.org/abs/2103.03423v2)** - [Code](https://github.com/tianyu0207/ccd) (confidence: high) * **[Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images](https://arxiv.org/abs/2012.07043v2)** - [Code](https://github.com/lwhyc/rpr-loc) (confidence: medium) * **[Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images](https://arxiv.org/abs/2010.00291v1)** - [Code](https://github.com/agaldran/cost_sensitive_loss_classification) (confidence: medium) * **[Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment](https://arxiv.org/abs/2008.09884v1)** - [Code](https://github.com/rayruizhiliao/joint_chestxray) (confidence: medium) * **[Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction](https://arxiv.org/abs/2007.13224v1)** - [Code](https://github.com/hasibzunair/uniformizing-3d) (confidence: medium) * **[Universal Loss Reweighting to Balance Lesion Size Inequality in 3D Medical Image Segmentation](https://arxiv.org/abs/2007.10033v1)** - [Code](https://github.com/neuro-ml/inverse_weighting) (confidence: medium) * **[Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration](https://arxiv.org/abs/2007.06959v1)** - [Code](https://github.com/jlianglab/semanticgenesis) (confidence: high) * **[Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet](https://arxiv.org/abs/2006.15954v2)** - [Code](https://github.com/raykoooo/cac-unet) (confidence: high) * **[AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation](https://arxiv.org/abs/2006.14858v1)** - [Code](https://github.com/meclabtuda/autosnap) (confidence: medium) * **[Boundary-assisted Region Proposal Networks for Nucleus Segmentation](https://arxiv.org/abs/2006.02695v1)** - [Code](https://github.com/csccsccsccsc/brpnet) (confidence: medium) * **[AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes](https://arxiv.org/abs/2005.01969v2)** - [Code](https://github.com/m3dv/alignshift) (confidence: medium) * **[Regression and Learning with Pixel-wise Attention for Retinal Fundus Glaucoma Segmentation and Detection](https://arxiv.org/abs/2001.01815v1)** - [Code](https://github.com/cswin/rlpa) (confidence: high) * **[Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response](https://arxiv.org/abs/1911.13077v1)** - [Code](https://github.com/naivete5656/wsispdr) (confidence: high) * **[Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation](https://arxiv.org/abs/1910.04961v2)** - [Code](https://github.com/yunyanxing/pairwise_xray_augmentation) (confidence: medium) * **[Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest x-rays](https://arxiv.org/abs/1908.10468v1)** - [Code](https://github.com/ricbl/vrgan) (confidence: medium) * **[Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells](https://arxiv.org/abs/1908.10109v1)** - [Code](https://github.com/kreshuklab/centriole_detection) (confidence: medium) * **[Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis](https://arxiv.org/abs/1908.06912v1)** - [Code](https://github.com/mrgiovanni/modelsgenesis) (confidence: medium) * **[MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation](https://arxiv.org/abs/1908.04373v1)** - [Code](https://github.com/rsummers11/cadlab) (confidence: high) * **[Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation](https://arxiv.org/abs/1907.13124v1)** - [Code](https://github.com/utkuozbulak/adaptive-segmentation-mask-attack) (confidence: medium) * **[NoduleNet: Decoupled False Positive Reductionfor Pulmonary Nodule Detection and Segmentation](https://arxiv.org/abs/1907.11320v1)** - [Code](https://github.com/uci-cbcl/nodulenet) (confidence: high) * **[Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes](https://arxiv.org/abs/1907.09140v2)** - [Code](https://github.com/yijingru/kg_instance_segmentation) (confidence: medium) * **[Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces](https://arxiv.org/abs/1907.05345v4)** - [Code](https://github.com/hzfu/eyeq) (confidence: medium) * **[INN: Inflated Neural Networks for IPMN Diagnosis](https://arxiv.org/abs/1907.00437v1)** - [Code](https://github.com/lalonderodney/inn-inflated-neural-nets) (confidence: medium) * **[Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection](https://arxiv.org/abs/1906.12225v2)** - [Code](https://github.com/quan14/modelling_airway_geometry_as_stock_market_data) (confidence: high) * **[Multi-Task Learning for Left Atrial Segmentation on GE-MRI](https://arxiv.org/abs/1810.13205v1)** - [Code](https://github.com/cherise215/atria_segmentation_2018) (confidence: medium) * **[MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation](https://arxiv.org/abs/1808.08180v3)** - [Code](https://github.com/camma-public/mvor) (confidence: medium) * **[CapsDeMM: Capsule network for Detection of Munro's Microabscess in skin biopsy images](https://arxiv.org/abs/1808.06428v2)** - [Code](https://github.com/anabik/capsdemm) (confidence: high) * **[3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection](https://arxiv.org/abs/1806.09648v2)** - [Code](https://github.com/rsummers11/cadlab) (confidence: high) * **[Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network](https://arxiv.org/abs/1806.07486v2)** - [Code](https://github.com/yuanwei1989/plane-detection) (confidence: high) * **[Fast Multiple Landmark Localisation Using a Patch-based Iterative Network](https://arxiv.org/abs/1806.06987v2)** - [Code](https://github.com/yuanwei1989/landmark-detection) (confidence: high) * **[Rotation Equivariant CNNs for Digital Pathology](https://arxiv.org/abs/1806.03962v1)** - [Code](https://github.com/basveeling/keras_gcnn) (confidence: medium) | [Code2](https://github.com/basveeling/pcam) * **[Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks](https://arxiv.org/abs/1804.08024v1)** - [Code](https://github.com/ternaus/angiodysplasia-segmentatio) (confidence: high) * **[HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation](https://arxiv.org/abs/1804.02967v2)** - [Code](https://github.com/josedolz/hyperdensenet) (confidence: medium) * **[Recognizing Surgical Activities with Recurrent Neural Networks](https://arxiv.org/abs/1606.06329v2)** - [Code](https://github.com/rdipietro/miccai-2016-surgical-activity-rec) (confidence: medium) ## 🔄 Image Registration *This list is automatically generated. See any issues? Please open a pull request!* * **[MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching](https://arxiv.org/abs/2606.28537v1)** - [Code](https://github.com/xypb/mammoflow) (confidence: medium) * **[3D Masked Autoencoders are Robust Learners of Volumetric and Multimodal Cellular Representations for Microscopy](https://arxiv.org/abs/2606.23964v1)** - [Code](https://github.com/marrlab/mae3d-opencell) (confidence: medium) * **[MedTS-TTT: Test-Time Training for Medical Time Series Classification](https://arxiv.org/abs/2606.21329v1)** - [Code](https://github.com/mingzhi-c/medts-ttt) (confidence: medium) * **[OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classification](https://arxiv.org/abs/2606.19838v1)** - [Code](https://github.com/labhai/otcha) (confidence: high) * **[Propagating Structural Guidance: Synthesizing Fluorescein Angiography from Fundus Images and Sparse OCT Scans](https://arxiv.org/abs/2606.16234v1)** - [Code](https://github.com/while-plus/oct-guide-ffa-syn) (confidence: medium) * **[WaveDiT: Distribution-Aware Wavelet Flow Matching for Efficient 3D Brain MRI Synthesis](https://arxiv.org/abs/2606.08670v1)** - [Code](https://github.com/sisinflab/wavedit) (confidence: medium) * **[Genetically Aligned Patient Representations Improve Hematological Diagnosis](https://arxiv.org/abs/2605.29980v1)** - [Code](https://github.com/marrlab/genbloom) (confidence: medium) * **[Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning](https://arxiv.org/abs/2605.26292v2)** - [Code](https://github.com/healthx-lab/evi-steer) (confidence: medium) * **[Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation](https://arxiv.org/abs/2605.25402v3)** - [Code](https://github.com/zhcz328/anaus) (confidence: medium) * **[Subspace-Guided Semantic and Topological Invariant Registration for Annotation-Free Ultrasound Plane Quality Control](https://arxiv.org/abs/2605.25396v1)** - [Code](https://github.com/zhcz328/striq) (confidence: high) * **[Exploiting Longitudinal Context in Clinician-Verified Interactive Lesion Tracking](https://arxiv.org/abs/2605.23118v1)** - [Code](https://github.com/mic-dkfz/longiseg) (confidence: medium) * **[Concept-Guided Noisy Negative Suppression for Zero-Shot Classification and Grounding of Chest X-Ray Findings](https://arxiv.org/abs/2605.19374v1)** - [Code](https://github.com/dopaminelcy/conns) (confidence: medium) * **[EchoTracker2: Enhancing Myocardial Point Tracking by Modeling Local Motion](https://arxiv.org/abs/2605.12140v1)** - [Code](https://github.com/riponazad/ptecho) (confidence: medium) * **[Unsupervised MR-US Multimodal Image Registration with Multilevel Correlation Pyramidal Optimization](https://arxiv.org/abs/2602.06288v2)** - [Code](https://github.com/wjiazheng/mcpo) (confidence: high) * **[MICCAI STSR 2025 Challenge: Semi-Supervised Teeth and Pulp Segmentation and CBCT-IOS Registration](https://arxiv.org/abs/2512.02867v1)** - [Code](https://github.com/ricoleehduu/sts-challenge-2025) (confidence: high) * **[US-X Complete: A Multi-Modal Approach to Anatomical 3D Shape Recovery](https://arxiv.org/abs/2511.15600v1)** - [Code](https://github.com/miruna20/us-x-complete) (confidence: medium) * **[Flip Distribution Alignment VAE for Multi-Phase MRI Synthesis](https://arxiv.org/abs/2510.02970v1)** - [Code](https://github.com/qianmuxiao/fda-vae) (confidence: high) * **[SpurBreast: A Curated Dataset for Investigating Spurious Correlations in Real-world Breast MRI Classification](https://arxiv.org/abs/2510.02109v1)** - [Code](https://github.com/utkuozbulak/spurbreast) (confidence: medium) * **[Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation](https://arxiv.org/abs/2509.13846v1)** - [Code](https://github.com/tenbatsu24/latentcampus) (confidence: high) * **[More performant and scalable: Rethinking contrastive vision-language pre-training of radiology in the LLM era](https://arxiv.org/abs/2509.13175v1)** - [Code](https://github.com/sadvoxel/more-performant-and-scalable) (confidence: medium) * **[SimCroP: Radiograph Representation Learning with Similarity-driven Cross-granularity Pre-training](https://arxiv.org/abs/2509.08311v1)** - [Code](https://github.com/tonichopp/simcrop) (confidence: medium) * **[Gaussian Primitive Optimized Deformable Retinal Image Registration](https://arxiv.org/abs/2508.16852v1)** - [Code](https://github.com/xintian-99/gporeg) (confidence: high) * **[Deep Biomechanically-Guided Interpolation for Keypoint-Based Brain Shift Registration](https://arxiv.org/abs/2508.13762v1)** - [Code](https://github.com/tiago-assis/deep-biomechanical-interpolator) (confidence: high) * **[Conditional Fetal Brain Atlas Learning for Automatic Tissue Segmentation](https://arxiv.org/abs/2508.04522v1)** - [Code](https://github.com/cirmuw/fetal-brain-atlas) (confidence: medium) * **[MCM: Mamba-based Cardiac Motion Tracking using Sequential Images in MRI](https://arxiv.org/abs/2507.17678v1)** - [Code](https://github.com/yjh-0104/mcm) (confidence: medium) * **[Dyna3DGR: 4D Cardiac Motion Tracking with Dynamic 3D Gaussian Representation](https://arxiv.org/abs/2507.16608v1)** - [Code](https://github.com/windrise/dyna3dgr) (confidence: high) * **[Text-driven Multiplanar Visual Interaction for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2507.12382v1)** - [Code](https://github.com/taozh2017/text-semiseg) (confidence: medium) * **[A Composite Alignment-Aware Framework for Myocardial Lesion Segmentation in Multi-sequence CMR Images](https://arxiv.org/abs/2507.11886v1)** - [Code](https://github.com/yifangao112/caa-seg) (confidence: high) * **[Cycle Context Verification for In-Context Medical Image Segmentation](https://arxiv.org/abs/2507.08357v1)** - [Code](https://github.com/shishuaihu/ccv) (confidence: medium) * **[Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transport](https://arxiv.org/abs/2507.04999v1)** - [Code](https://github.com/qinkaiyu/rima) (confidence: high) * **[Unsupervised Cardiac Video Translation Via Motion Feature Guided Diffusion Model](https://arxiv.org/abs/2507.02003v2)** - [Code](https://github.com/swakshardeb/mfd-v2v) (confidence: medium) * **[TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency](https://arxiv.org/abs/2507.00802v2)** - [Code](https://github.com/vinyehshaw/trace) (confidence: medium) * **[MadCLIP: Few-shot Medical Anomaly Detection with CLIP](https://arxiv.org/abs/2506.23810v1)** - [Code](https://github.com/mahshid1998/madclip) (confidence: medium) * **[SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting](https://arxiv.org/abs/2506.23309v2)** - [Code](https://github.com/lastbasket/surgtpgs) (confidence: medium) * **[FedCLAM: Client Adaptive Momentum with Foreground Intensity Matching for Federated Medical Image Segmentation](https://arxiv.org/abs/2506.22580v1)** - [Code](https://github.com/siomvas/fedclam) (confidence: medium) * **[DIGS: Dynamic CBCT Reconstruction using Deformation-Informed 4D Gaussian Splatting and a Low-Rank Free-Form Deformation Model](https://arxiv.org/abs/2506.22280v1)** - [Code](https://github.com/yuliang-huang/digs) (confidence: high) * **[Cardiovascular disease classification using radiomics and geometric features from cardiac CT](https://arxiv.org/abs/2506.22226v2)** - [Code](https://github.com/biomedia-mira/grc-net) (confidence: high) * **[VoxelOpt: Voxel-Adaptive Message Passing for Discrete Optimization in Deformable Abdominal CT Registration](https://arxiv.org/abs/2506.19975v1)** - [Code](https://github.com/tinymilky/voxelopt) (confidence: high) * **[Global and Local Contrastive Learning for Joint Representations from Cardiac MRI and ECG](https://arxiv.org/abs/2506.20683v1)** - [Code](https://github.com/alsalivan/ecgcmr) (confidence: medium) * **[Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction](https://arxiv.org/abs/2506.19363v1)** - [Code](https://github.com/sot176/longitudinal_mammogram_alignment) (confidence: high) * **[Continual Retinal Vision-Language Pre-training upon Incremental Imaging Modalities](https://arxiv.org/abs/2506.19320v1)** - [Code](https://github.com/yuang-yao/retcop) (confidence: medium) * **[Mono-Modalizing Extremely Heterogeneous Multi-Modal Medical Image Registration](https://arxiv.org/abs/2506.15596v2)** - [Code](https://github.com/micv-yonsei/m2m-reg) (confidence: high) * **[Guiding Registration with Emergent Similarity from Pre-Trained Diffusion Models](https://arxiv.org/abs/2506.02419v1)** - [Code](https://github.com/uncbiag/dgir) (confidence: high) * **[Holistic White-light Polyp Classification via Alignment-free Dense Distillation of Auxiliary Optical Chromoendoscopy](https://arxiv.org/abs/2505.19319v3)** - [Code](https://github.com/huster-hq/add) (confidence: high) * **[Adaptive Spatial Transcriptomics Interpolation via Cross-modal Cross-slice Modeling](https://arxiv.org/abs/2505.10729v1)** - [Code](https://github.com/xiaofeiwang2018/c2-sti) (confidence: medium) * **[CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention](https://arxiv.org/abs/2503.15949v1)** - [Code](https://github.com/wutcm-lab/causalclipseg) (confidence: medium) * **[UniCrossAdapter: Multimodal Adaptation of CLIP for Radiology Report Generation](https://arxiv.org/abs/2503.15940v1)** - [Code](https://github.com/chauncey-tow/mrg-clip) (confidence: medium) * **[Generating Novel Brain Morphology by Deforming Learned Templates](https://arxiv.org/abs/2503.03778v3)** - [Code](https://github.com/alanqrwang/morphldm) (confidence: high) * **[RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment](https://arxiv.org/abs/2501.07525v2)** - [Code](https://github.com/difeigu/radalign) (confidence: high) * **[Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation](https://arxiv.org/abs/2411.15490v3)** - [Code](https://github.com/jhlee0619/pirta) (confidence: medium) * **[Graph Neural Networks for modelling breast biomechanical compression](https://arxiv.org/abs/2411.06596v1)** - [Code](https://github.com/hadiiiil/gnns-breastcompression) (confidence: high) * **[DiffuseReg: Denoising Diffusion Model for Obtaining Deformation Fields in Unsupervised Deformable Image Registration](https://arxiv.org/abs/2410.05234v1)** - [Code](https://github.com/yutazhuo/diffusereg) (confidence: high) * **[Optimising for the Unknown: Domain Alignment for Cephalometric Landmark Detection](https://arxiv.org/abs/2410.04445v1)** - [Code](https://github.com/julian-wyatt/optimisingfortheunknown) (confidence: high) * **[Unsupervised Multimodal 3D Medical Image Registration with Multilevel Correlation Balanced Optimization](https://arxiv.org/abs/2409.05040v2)** - [Code](https://github.com/wjiazheng/mcbo) (confidence: high) * **[PatchAlign:Fair and Accurate Skin Disease Image Classification by Alignment with Clinical Labels](https://arxiv.org/abs/2409.04975v1)** - [Code](https://github.com/aayushmanace/patchalign24) (confidence: high) * **[A Review of 3D Reconstruction Techniques for Deformable Tissues in Robotic Surgery](https://arxiv.org/abs/2408.04426v1)** - [Code](https://github.com/epsilon404/surgicalnerf) (confidence: high) * **[Segmentation Style Discovery: Application to Skin Lesion Images](https://arxiv.org/abs/2408.02787v1)** - [Code](https://github.com/sfu-mial/styleseg) (confidence: medium) * **[Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation](https://arxiv.org/abs/2407.21490v1)** - [Code](https://github.com/mlmi-2024-72/ecm) (confidence: medium) * **[CoMoTo: Unpaired Cross-Modal Lesion Distillation Improves Breast Lesion Detection in Tomosynthesis](https://arxiv.org/abs/2407.17620v1)** - [Code](https://github.com/muhammad-al-barbary/comoto) (confidence: medium) * **[WiNet: Wavelet-based Incremental Learning for Efficient Medical Image Registration](https://arxiv.org/abs/2407.13426v1)** - [Code](https://github.com/x-xc/winet) (confidence: high) * **[TLRN: Temporal Latent Residual Networks For Large Deformation Image Registration](https://arxiv.org/abs/2407.11219v3)** - [Code](https://github.com/nellie689/tlrn) (confidence: high) * **[Nonrigid Reconstruction of Freehand Ultrasound without a Tracker](https://arxiv.org/abs/2407.05767v2)** - [Code](https://github.com/qili111/nr-rec-fus) (confidence: high) * **[Self-Paced Sample Selection for Barely-Supervised Medical Image Segmentation](https://arxiv.org/abs/2407.05248v1)** - [Code](https://github.com/suuujm/spss) (confidence: medium) * **[Data-Driven Tissue- and Subject-Specific Elastic Regularization for Medical Image Registration](https://arxiv.org/abs/2407.04355v1)** - [Code](https://github.com/compai-lab/2024-miccai-reithmeir) (confidence: high) * **[Centerline Boundary Dice Loss for Vascular Segmentation](https://arxiv.org/abs/2407.01517v1)** - [Code](https://github.com/pengchengshi1220/cbdice) (confidence: medium) * **[Toward Universal Medical Image Registration via Sharpness-Aware Meta-Continual Learning](https://arxiv.org/abs/2406.17575v1)** - [Code](https://github.com/xzluo97/continual-reg) (confidence: high) * **[Groupwise Deformable Registration of Diffusion Tensor Cardiovascular Magnetic Resonance: Disentangling Diffusion Contrast, Respiratory and Cardiac Motions](https://arxiv.org/abs/2406.13788v2)** - [Code](https://github.com/ayanglab/dtcmr-reg) (confidence: high) * **[SALI: Short-term Alignment and Long-term Interaction Network for Colonoscopy Video Polyp Segmentation](https://arxiv.org/abs/2406.13532v1)** - [Code](https://github.com/scatteredrain/sali) (confidence: high) * **[Cephalometric Landmark Detection across Ages with Prototypical Network](https://arxiv.org/abs/2406.12577v1)** - [Code](https://github.com/shanghaitech-impact/cephalometric-landmark-detection-across-ages-with-prototypical-network) (confidence: medium) * **[Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations](https://arxiv.org/abs/2406.06384v1)** - [Code](https://github.com/richard-peng-xia/deco) (confidence: medium) * **[Deform3DGS: Flexible Deformation for Fast Surgical Scene Reconstruction with Gaussian Splatting](https://arxiv.org/abs/2405.17835v3)** - [Code](https://github.com/jinlab-imvr/deform3dgs) (confidence: high) * **[Eddeep: Fast eddy-current distortion correction for diffusion MRI with deep learning](https://arxiv.org/abs/2405.10723v3)** - [Code](https://github.com/cig-ucl/eddeep) (confidence: medium) * **[EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting](https://arxiv.org/abs/2401.11535v3)** - [Code](https://github.com/hku-medai/endogs) (confidence: high) * **[ASC: Appearance and Structure Consistency for Unsupervised Domain Adaptation in Fetal Brain MRI Segmentation](https://arxiv.org/abs/2310.14172v1)** - [Code](https://github.com/lhaof/asc) (confidence: medium) * **[Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration](https://arxiv.org/abs/2310.11040v3)** - [Code](https://github.com/brain-intelligence-lab/girnet) (confidence: high) * **[A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos](https://arxiv.org/abs/2309.04702v1)** - [Code](https://github.com/alfredqin/stnet) (confidence: high) * **[On the Localization of Ultrasound Image Slices within Point Distribution Models](https://arxiv.org/abs/2309.00372v1)** - [Code](https://github.com/vuenc/slice-to-shape) (confidence: medium) * **[Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment](https://arxiv.org/abs/2308.16735v1)** - [Code](https://github.com/felixwag/staralign) (confidence: high) * **[On-the-Fly Guidance Training for Medical Image Registration](https://arxiv.org/abs/2308.15216v5)** - [Code](https://github.com/cilix-ai/on-the-fly-guidance) (confidence: high) * **[DETDet: Dual Ensemble Teeth Detection](https://arxiv.org/abs/2308.14070v1)** - [Code](https://github.com/bestever-choi/evident) (confidence: medium) * **[TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction](https://arxiv.org/abs/2308.12443v1)** - [Code](https://github.com/gxq1998/tai-gan) (confidence: medium) * **[PCMC-T1: Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction](https://arxiv.org/abs/2308.11281v1)** - [Code](https://github.com/eyalhana/pcmc-t1) (confidence: high) * **[Fundus-Enhanced Disease-Aware Distillation Model for Retinal Disease Classification from OCT Images](https://arxiv.org/abs/2308.00291v1)** - [Code](https://github.com/xmed-lab/fddm) (confidence: medium) * **[Cross-Dataset Adaptation for Instrument Classification in Cataract Surgery Videos](https://arxiv.org/abs/2308.04035v1)** - [Code](https://github.com/jayparanjape/barlow-adaptor) (confidence: medium) * **[FSDiffReg: Feature-wise and Score-wise Diffusion-guided Unsupervised Deformable Image Registration for Cardiac Images](https://arxiv.org/abs/2307.12035v1)** - [Code](https://github.com/xmed-lab/fsdiffreg) (confidence: high) * **[EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos](https://arxiv.org/abs/2307.11307v2)** - [Code](https://github.com/ruyi-zha/endosurf) (confidence: high) * **[Unsupervised 3D registration through optimization-guided cyclical self-training](https://arxiv.org/abs/2306.16997v2)** - [Code](https://github.com/multimodallearning/reg-cyclical-self-train) (confidence: high) * **[A denoised Mean Teacher for domain adaptive point cloud registration](https://arxiv.org/abs/2306.14749v2)** - [Code](https://github.com/multimodallearning/denoised_mt_pcd_reg) (confidence: high) * **[ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer](https://arxiv.org/abs/2306.05688v1)** - [Code](https://github.com/zax130/smilecode) (confidence: high) * **[DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models](https://arxiv.org/abs/2304.13416v2)** - [Code](https://github.com/shaoshitong/diffuseexpand) (confidence: medium) * **[Recurrence With Correlation Network for Medical Image Registration](https://arxiv.org/abs/2302.02283v1)** - [Code](https://github.com/vigsivan/optimization-based-registration) (confidence: high) * **[CircleSnake: Instance Segmentation with Circle Representation](https://arxiv.org/abs/2211.01254v1)** - [Code](https://github.com/hrlblab/circlesnake) (confidence: medium) * **[Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://arxiv.org/abs/2209.06861v1)** - [Code](https://github.com/davecasp/flowssm) (confidence: medium) * **[Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging](https://arxiv.org/abs/2208.12737v1)** - [Code](https://github.com/v715/diffdrr) (confidence: medium) * **[CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays](https://arxiv.org/abs/2208.03873v2)** - [Code](https://github.com/plan-lab/chexrelnet) (confidence: medium) * **[U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?](https://arxiv.org/abs/2208.04939v2)** - [Code](https://github.com/xi-jia/lku-net) (confidence: high) * **[Automatic Segmentation of the Placenta in BOLD MRI Time Series](https://arxiv.org/abs/2208.02895v1)** - [Code](https://github.com/mabulnaga/automatic-placenta-segmentation) (confidence: high) * **[Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI](https://arxiv.org/abs/2207.02390v1)** - [Code](https://github.com/ayanglab/sdaut) (confidence: high) * **[Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts](https://arxiv.org/abs/2207.00371v1)** - [Code](https://github.com/multimodallearning/registration-da-mean-teacher) (confidence: high) * **[XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention](https://arxiv.org/abs/2206.07349v1)** - [Code](https://github.com/solemoon/xmorpher) (confidence: high) * **[Transformer Lesion Tracker](https://arxiv.org/abs/2206.06252v1)** - [Code](https://github.com/tangwen920812/tlt) (confidence: medium) * **[Cross-modal Attention for MRI and Ultrasound Volume Registration](https://arxiv.org/abs/2107.04548v2)** - [Code](https://github.com/dial-rpi/attention-reg) (confidence: high) * **[Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning](https://arxiv.org/abs/2105.12722v2)** - [Code](https://github.com/pakheiyeung/sli2vol) (confidence: medium) * **[Deep learning based registration using spatial gradients and noisy segmentation labels](https://arxiv.org/abs/2010.10897v2)** - [Code](https://github.com/theoest/abdominal_registration) (confidence: high) | [Code2](https://github.com/theoest/hippocampus_registration) * **[3D Reconstruction and Segmentation of Dissection Photographs for MRI-free Neuropathology](https://arxiv.org/abs/2009.05596v1)** - [Code](https://github.com/htregidgo/dissectionphotovolumes) (confidence: medium) * **[Anatomical Data Augmentation via Fluid-based Image Registration](https://arxiv.org/abs/2007.02447v1)** - [Code](https://github.com/uncbiag/easyreg) (confidence: high) * **[MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation](https://arxiv.org/abs/2006.15573v2)** - [Code](https://github.com/xzluo97/mvmm-regnet) (confidence: high) * **[Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks](https://arxiv.org/abs/1907.10931v1)** - [Code](https://github.com/multimodallearning/pdd_net) (confidence: high) * **[Image-and-Spatial Transformer Networks for Structure-Guided Image Registration](https://arxiv.org/abs/1907.09200v1)** - [Code](https://github.com/biomedia-mira/istn) (confidence: high) ## 🔀 Domain Adaptation *This list is automatically generated. See any issues? Please open a pull request!* * **[MedTS-TTT: Test-Time Training for Medical Time Series Classification](https://arxiv.org/abs/2606.21329v1)** - [Code](https://github.com/mingzhi-c/medts-ttt) (confidence: medium) * **[Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning](https://arxiv.org/abs/2605.26292v2)** - [Code](https://github.com/healthx-lab/evi-steer) (confidence: high) * **[Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation](https://arxiv.org/abs/2605.25402v3)** - [Code](https://github.com/zhcz328/anaus) (confidence: medium) * **[Adaptive Stain Normalization for Cross-Domain Medical Histology](https://arxiv.org/abs/2510.06592v1)** - [Code](https://github.com/xutianyue/beerlanet) (confidence: high) * **[Disentanglement of Biological and Technical Factors via Latent Space Rotation in Clinical Imaging Improves Disease Pattern Discovery](https://arxiv.org/abs/2509.11436v1)** - [Code](https://github.com/cirmuw/latent-space-rotation-disentanglement) (confidence: medium) * **[Leveraging Generic Foundation Models for Multimodal Surgical Data Analysis](https://arxiv.org/abs/2509.06831v1)** - [Code](https://github.com/digitalsurgerylab-basel/ml-cds-2025) (confidence: high) * **[HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters](https://arxiv.org/abs/2508.13026v1)** - [Code](https://github.com/ruru-xu/hieradaptmr) (confidence: medium) * **[MAUP: Training-free Multi-center Adaptive Uncertainty-aware Prompting for Cross-domain Few-shot Medical Image Segmentation](https://arxiv.org/abs/2508.03511v1)** - [Code](https://github.com/yazhouzhu19/maup) (confidence: high) * **[Trustworthy Few-Shot Transfer of Medical VLMs through Split Conformal Prediction](https://arxiv.org/abs/2506.17503v1)** - [Code](https://github.com/jusiro/sca-t) (confidence: medium) * **[Holistic White-light Polyp Classification via Alignment-free Dense Distillation of Auxiliary Optical Chromoendoscopy](https://arxiv.org/abs/2505.19319v3)** - [Code](https://github.com/huster-hq/add) (confidence: medium) * **[UniCrossAdapter: Multimodal Adaptation of CLIP for Radiology Report Generation](https://arxiv.org/abs/2503.15940v1)** - [Code](https://github.com/chauncey-tow/mrg-clip) (confidence: medium) * **[Are ECGs enough? Deep learning classification of pulmonary embolism using electrocardiograms](https://arxiv.org/abs/2503.08960v2)** - [Code](https://github.com/joaodsmarques/are-ecgs-enough-deep-learning-classifiers) (confidence: medium) * **[FACMIC: Federated Adaptative CLIP Model for Medical Image Classification](https://arxiv.org/abs/2410.14707v1)** - [Code](https://github.com/aipmlab/facmic) (confidence: medium) * **[Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2409.12522v1)** - [Code](https://github.com/wkklavis/dapsam) (confidence: high) * **[PatchAlign:Fair and Accurate Skin Disease Image Classification by Alignment with Clinical Labels](https://arxiv.org/abs/2409.04975v1)** - [Code](https://github.com/aayushmanace/patchalign24) (confidence: medium) * **[CROCODILE: Causality aids RObustness via COntrastive DIsentangled LEarning](https://arxiv.org/abs/2408.04949v1)** - [Code](https://github.com/gianlucarloni/crocodile) (confidence: high) * **[Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis](https://arxiv.org/abs/2408.03035v2)** - [Code](https://github.com/gungui98/echo-free) (confidence: medium) * **[Lesion Elevation Prediction from Skin Images Improves Diagnosis](https://arxiv.org/abs/2408.02792v1)** - [Code](https://github.com/sfu-mial/lesionelevation) (confidence: high) * **[AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation](https://arxiv.org/abs/2408.00640v2)** - [Code](https://github.com/asbjrnmunk/amaes) (confidence: high) * **[Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization](https://arxiv.org/abs/2407.02900v1)** - [Code](https://github.com/sdoerrich97/vits-are-generative-models) (confidence: high) * **[An Uncertainty-guided Tiered Self-training Framework for Active Source-free Domain Adaptation in Prostate Segmentation](https://arxiv.org/abs/2407.02893v2)** - [Code](https://github.com/hilab-git/ugtst) (confidence: high) * **[MedMNIST-C: Comprehensive benchmark and improved classifier robustness by simulating realistic image corruptions](https://arxiv.org/abs/2406.17536v3)** - [Code](https://github.com/francescodisalvo05/medmnistc-api) (confidence: high) * **[Advancing UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation and a Novel Multi-Center Dataset](https://arxiv.org/abs/2406.13645v1)** - [Code](https://github.com/whq-xxh/sfada-uwf-slo) (confidence: high) * **[Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation](https://arxiv.org/abs/2405.16102v1)** - [Code](https://github.com/zenghy96/reliable-source-approximation) (confidence: high) * **[Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification](https://arxiv.org/abs/2405.19346v2)** - [Code](https://github.com/sionan/miccai2024-restl) (confidence: high) * **[Can LLMs' Tuning Methods Work in Medical Multimodal Domain?](https://arxiv.org/abs/2403.06407v2)** - [Code](https://github.com/timmy-chan/mile) (confidence: medium) * **[MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation](https://arxiv.org/abs/2402.17725v2)** - [Code](https://github.com/hananshafi/medcontext) (confidence: medium) * **[Histopathological Image Analysis with Style-Augmented Feature Domain Mixing for Improved Generalization](https://arxiv.org/abs/2310.20638v1)** - [Code](https://github.com/vaibhav-khamankar/fusestyle) (confidence: high) * **[ASC: Appearance and Structure Consistency for Unsupervised Domain Adaptation in Fetal Brain MRI Segmentation](https://arxiv.org/abs/2310.14172v1)** - [Code](https://github.com/lhaof/asc) (confidence: high) * **[Unsupervised Domain Adaptation for Anatomical Landmark Detection](https://arxiv.org/abs/2308.13286v1)** - [Code](https://github.com/jhb86253817/uda_med_landmark) (confidence: high) * **[Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation](https://arxiv.org/abs/2308.07731v1)** - [Code](https://github.com/xmed-lab/cpr) (confidence: high) * **[Cross-Dataset Adaptation for Instrument Classification in Cataract Surgery Videos](https://arxiv.org/abs/2308.04035v1)** - [Code](https://github.com/jayparanjape/barlow-adaptor) (confidence: high) * **[Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation](https://arxiv.org/abs/2307.03008v3)** - [Code](https://github.com/j-morano/multimodal-ssl-fpn) (confidence: medium) * **[Semi-supervised Domain Adaptive Medical Image Segmentation through Consistency Regularized Disentangled Contrastive Learning](https://arxiv.org/abs/2307.02798v1)** - [Code](https://github.com/hritam-98/gfda-disentangled) (confidence: high) * **[Unsupervised 3D registration through optimization-guided cyclical self-training](https://arxiv.org/abs/2306.16997v2)** - [Code](https://github.com/multimodallearning/reg-cyclical-self-train) (confidence: medium) * **[Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train](https://arxiv.org/abs/2306.16741v4)** - [Code](https://github.com/med-air/endo-fm) (confidence: medium) * **[A denoised Mean Teacher for domain adaptive point cloud registration](https://arxiv.org/abs/2306.14749v2)** - [Code](https://github.com/multimodallearning/denoised_mt_pcd_reg) (confidence: medium) * **[Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation](https://arxiv.org/abs/2306.05254v2)** - [Code](https://github.com/shishuaihu/ccsdg) (confidence: high) * **[DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2306.00499v2)** - [Code](https://github.com/yifangao112/desam) (confidence: high) * **[Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentation](https://arxiv.org/abs/2305.19949v1)** - [Code](https://github.com/chen-ziyang/trid) (confidence: high) * **[Distilling BlackBox to Interpretable models for Efficient Transfer Learning](https://arxiv.org/abs/2305.17303v7)** - [Code](https://github.com/batmanlab/miccai-2023-route-interpret-repeat-cxrs) (confidence: high) * **[EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition](https://arxiv.org/abs/2304.01508v3)** - [Code](https://github.com/siyuanyan1/epvt) (confidence: high) * **[Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation](https://arxiv.org/abs/2303.05785v2)** - [Code](https://github.com/masilab/repux-net) (confidence: medium) * **[Motion-related Artefact Classification Using Patch-based Ensemble and Transfer Learning in Cardiac MRI](https://arxiv.org/abs/2210.07717v1)** - [Code](https://github.com/ruizhe-l/cmrxmotion) (confidence: high) * **[3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation](https://arxiv.org/abs/2209.15076v4)** - [Code](https://github.com/masilab/3dux-net) (confidence: medium) * **[Noise transfer for unsupervised domain adaptation of retinal OCT images](https://arxiv.org/abs/2209.08097v1)** - [Code](https://github.com/valentinkoch/svdna) (confidence: high) * **[Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning](https://arxiv.org/abs/2208.08226v2)** - [Code](https://github.com/miccai2022-155/autoseg) (confidence: high) * **[Deep Laparoscopic Stereo Matching with Transformers](https://arxiv.org/abs/2207.12152v1)** - [Code](https://github.com/xueliancheng/hybridstereonet-main) (confidence: medium) * **[Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach](https://arxiv.org/abs/2207.00844v1)** - [Code](https://github.com/winstonhutiger/2d_vae_uda_for_3d_sythesis) (confidence: high) * **[Adapting the Mean Teacher for keypoint-based lung registration under geometric domain shifts](https://arxiv.org/abs/2207.00371v1)** - [Code](https://github.com/multimodallearning/registration-da-mean-teacher) (confidence: high) * **[MaNi: Maximizing Mutual Information for Nuclei Cross-Domain Unsupervised Segmentation](https://arxiv.org/abs/2206.14437v1)** - [Code](https://github.com/yashsharma/mani) (confidence: high) * **[Automatic identification of segmentation errors for radiotherapy using geometric learning](https://arxiv.org/abs/2206.13317v1)** - [Code](https://github.com/rrr-uom-projects/contour_auto_qatool) (confidence: medium) * **[MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels](https://arxiv.org/abs/2203.12454v1)** - [Code](https://github.com/jacobzhaoziyuan/mt-uda) (confidence: high) * **[Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture Classification](https://arxiv.org/abs/2110.10383v1)** - [Code](https://github.com/ljaiverson/multiview-curriculum) (confidence: medium) * **[A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis](https://arxiv.org/abs/2108.05930v1)** - [Code](https://github.com/jlianglab/benchmarktransferlearning) (confidence: high) * **[Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation](https://arxiv.org/abs/2107.11091v1)** - [Code](https://github.com/xumengyaamy/cidacaptioning) (confidence: high) * **[Few-Shot Domain Adaptation with Polymorphic Transformers](https://arxiv.org/abs/2107.04805v1)** - [Code](https://github.com/askerlee/segtran) (confidence: high) * **[Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation](https://arxiv.org/abs/2107.03887v1)** - [Code](https://github.com/shuowang26/srheart) (confidence: medium) * **[Histogram Matching Augmentation for Domain Adaptation with Application to Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Image Segmentation](https://arxiv.org/abs/2012.13871v1)** - [Code](https://github.com/junma11/hm_dataaug) (confidence: high) * **[Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation](https://arxiv.org/abs/2010.07411v2)** - [Code](https://github.com/elchiou/da) (confidence: high) * **[Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration](https://arxiv.org/abs/2007.06959v1)** - [Code](https://github.com/jlianglab/semanticgenesis) (confidence: medium) * **[Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains](https://arxiv.org/abs/2007.02035v1)** - [Code](https://github.com/liuquande/saml) (confidence: high) * **[VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images](https://arxiv.org/abs/2001.09193v6)** - [Code](https://github.com/anjany/verse) (confidence: medium) * **[Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis](https://arxiv.org/abs/1908.06912v1)** - [Code](https://github.com/mrgiovanni/modelsgenesis) (confidence: medium) * **[Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation](https://arxiv.org/abs/1906.11143v2)** - [Code](https://github.com/emmaw8/beal) (confidence: high) ## 🎨 Generative Models *This list is automatically generated. See any issues? Please open a pull request!* * **[MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching](https://arxiv.org/abs/2606.28537v1)** - [Code](https://github.com/xypb/mammoflow) (confidence: high) * **[Anatomy-Grounded Synthetic Coronary Angiography for Geometry-Informed Multi-View Matching](https://arxiv.org/abs/2606.28474v1)** - [Code](https://github.com/medipixel/gimm) (confidence: medium) * **[Beyond Visual Forensics: Auditing Multimodal Robustness for Synthetic Medical Image Detection](https://arxiv.org/abs/2606.25375v1)** - [Code](https://github.com/chiuhaohao/beyond-visual-forensics) (confidence: medium) * **[NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction](https://arxiv.org/abs/2606.24087v1)** - [Code](https://github.com/y-research-sbu/neurosonic) (confidence: high) * **[MaRS: Robust Out-of-Distribution Detection via Mahalanobis Residual Scoring](https://arxiv.org/abs/2606.22649v2)** - [Code](https://github.com/francescodisalvo05/mars) (confidence: medium) * **[One-Shot Data Selection for Medical Image Classification via Graph Coverage](https://arxiv.org/abs/2606.22002v1)** - [Code](https://github.com/zahiriddin-rustamov/graph-coverage-selection) (confidence: medium) * **[Single-Stage Hierarchical Rectification for Weakly Supervised Histopathology Segmentation](https://arxiv.org/abs/2606.20250v1)** - [Code](https://github.com/trongduc-nguyen/sshr) (confidence: medium) * **[A Multi-Center Benchmark for Abdominal Disease Diagnosis and Report Generation from Non-Contrast CT](https://arxiv.org/abs/2606.16991v1)** - [Code](https://github.com/xmed-lab/trials-report) (confidence: high) * **[Propagating Structural Guidance: Synthesizing Fluorescein Angiography from Fundus Images and Sparse OCT Scans](https://arxiv.org/abs/2606.16234v1)** - [Code](https://github.com/while-plus/oct-guide-ffa-syn) (confidence: medium) * **[WaveDiT: Distribution-Aware Wavelet Flow Matching for Efficient 3D Brain MRI Synthesis](https://arxiv.org/abs/2606.08670v1)** - [Code](https://github.com/sisinflab/wavedit) (confidence: high) * **[BrainAnytime: Anatomy-Aware Cross-Modal Pretraining for Brain Image Analysis with Arbitrary Modality Availability](https://arxiv.org/abs/2605.13059v1)** - [Code](https://github.com/sdh-lab/brainanytime) (confidence: medium) * **[ScribbleDose: Scribble-Guided Dose Prediction in Radiotherapy](https://arxiv.org/abs/2605.11555v2)** - [Code](https://github.com/icherishxixixi/scribbledose) (confidence: medium) * **[Exemplar Diffusion: Improving Medical Object Detection with Opportunistic Labels](https://arxiv.org/abs/2603.15267v1)** - [Code](https://github.com/waahlstrand/exemplardiffusion) (confidence: high) * **[EchoLVFM: One-Step Video Generation via Latent Flow Matching for Echocardiogram Synthesis](https://arxiv.org/abs/2603.13967v1)** - [Code](https://github.com/engemmanuel/echolvfm) (confidence: high) * **[DUCX: Decomposing Unfairness in Tool-Using Chest X-ray Agents](https://arxiv.org/abs/2603.00777v2)** - [Code](https://github.com/nanboy-ronan/duck) (confidence: medium) * **[TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration](https://arxiv.org/abs/2512.14550v1)** - [Code](https://github.com/yaziwel/tat) (confidence: high) * **[SSL-MedSAM2: A Semi-supervised Medical Image Segmentation Framework Powered by Few-shot Learning of SAM2](https://arxiv.org/abs/2512.11548v1)** - [Code](https://github.com/naisops/ssl-medsam2) (confidence: medium) * **[Benchmark-Ready 3D Anatomical Shape Classification](https://arxiv.org/abs/2511.01613v1)** - [Code](https://github.com/tomaskrsicka/medshapenet19-pspooling) (confidence: medium) * **[Flip Distribution Alignment VAE for Multi-Phase MRI Synthesis](https://arxiv.org/abs/2510.02970v1)** - [Code](https://github.com/qianmuxiao/fda-vae) (confidence: high) * **[Segmentor-Guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis](https://arxiv.org/abs/2509.24913v2)** - [Code](https://github.com/biomedia-mira/seg-cft) (confidence: high) * **[U-Mamba2-SSL for Semi-Supervised Tooth and Pulp Segmentation in CBCT](https://arxiv.org/abs/2509.20154v2)** - [Code](https://github.com/zhiqin1998/umamba2) (confidence: medium) * **[Echo-Path: Pathology-Conditioned Echo Video Generation](https://arxiv.org/abs/2509.17190v1)** - [Code](https://github.com/marshall-mk/echopathv1) (confidence: high) * **[SLaM-DiMM: Shared Latent Modeling for Diffusion Based Missing Modality Synthesis in MRI](https://arxiv.org/abs/2509.16019v1)** - [Code](https://github.com/bheeshmsharma/slam-dimm-miccai-brats-challenge-2025) (confidence: high) * **[Semantic Diffusion Posterior Sampling for Cardiac Ultrasound Dehazing](https://arxiv.org/abs/2508.17326v1)** - [Code](https://github.com/tristan-deep/semantic-diffusion-echo-dehazing) (confidence: high) * **[Tooth-Diffusion: Guided 3D CBCT Synthesis with Fine-Grained Tooth Conditioning](https://arxiv.org/abs/2508.14276v1)** - [Code](https://github.com/djafar1/tooth-diffusion) (confidence: high) * **[Comparing Conditional Diffusion Models for Synthesizing Contrast-Enhanced Breast MRI from Pre-Contrast Images](https://arxiv.org/abs/2508.13776v2)** - [Code](https://github.com/sebastibar/conditional-diffusion-breast-mri) (confidence: high) * **[Cross-view Generalized Diffusion Model for Sparse-view CT Reconstruction](https://arxiv.org/abs/2508.10313v1)** - [Code](https://github.com/xmed-lab/cvg-diff) (confidence: high) * **[Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging](https://arxiv.org/abs/2508.10132v1)** - [Code](https://github.com/hawaii-ai/dxa-pointplacement) (confidence: medium) * **[MAUP: Training-free Multi-center Adaptive Uncertainty-aware Prompting for Cross-domain Few-shot Medical Image Segmentation](https://arxiv.org/abs/2508.03511v1)** - [Code](https://github.com/yazhouzhu19/maup) (confidence: medium) * **[GL-LCM: Global-Local Latent Consistency Models for Fast High-Resolution Bone Suppression in Chest X-Ray Images](https://arxiv.org/abs/2508.03357v1)** - [Code](https://github.com/diaoquesang/gl-lcm) (confidence: medium) * **[REFLECT: Rectified Flows for Efficient Brain Anomaly Correction Transport](https://arxiv.org/abs/2508.02889v1)** - [Code](https://github.com/farzad-bz/reflect) (confidence: medium) * **[Diffusion-Based User-Guided Data Augmentation for Coronary Stenosis Detection](https://arxiv.org/abs/2508.00438v1)** - [Code](https://github.com/medipixel/digda) (confidence: high) * **[$MV_{Hybrid}$: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Models](https://arxiv.org/abs/2508.00383v1)** - [Code](https://github.com/deepnoid-ai/mvhybrid) (confidence: medium) * **[EndoGen: Conditional Autoregressive Endoscopic Video Generation](https://arxiv.org/abs/2507.17388v1)** - [Code](https://github.com/cuhk-aim-group/endogen) (confidence: high) * **[Parameterized Diffusion Optimization enabled Autoregressive Ordinal Regression for Diabetic Retinopathy Grading](https://arxiv.org/abs/2507.04978v1)** - [Code](https://github.com/qinkaiyu/aor-dr) (confidence: high) * **[Unsupervised Cardiac Video Translation Via Motion Feature Guided Diffusion Model](https://arxiv.org/abs/2507.02003v2)** - [Code](https://github.com/swakshardeb/mfd-v2v) (confidence: high) * **[TRACE: Temporally Reliable Anatomically-Conditioned 3D CT Generation with Enhanced Efficiency](https://arxiv.org/abs/2507.00802v2)** - [Code](https://github.com/vinyehshaw/trace) (confidence: high) * **[Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructions](https://arxiv.org/abs/2507.00670v1)** - [Code](https://github.com/nikolasmorshuis/sdr) (confidence: medium) * **[$μ^2$Tokenizer: Differentiable Multi-Scale Multi-Modal Tokenizer for Radiology Report Generation](https://arxiv.org/abs/2507.00316v2)** - [Code](https://github.com/siyou-li/u2tokenizer) (confidence: high) * **[Uncertainty-aware Diffusion and Reinforcement Learning for Joint Plane Localization and Anomaly Diagnosis in 3D Ultrasound](https://arxiv.org/abs/2506.23538v2)** - [Code](https://github.com/yuhoo0302/cua-us) (confidence: high) * **[SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting](https://arxiv.org/abs/2506.23309v2)** - [Code](https://github.com/lastbasket/surgtpgs) (confidence: medium) * **[Exploring the Design Space of 3D MLLMs for CT Report Generation](https://arxiv.org/abs/2506.21535v2)** - [Code](https://github.com/bowang-lab/amos-mm-solution) (confidence: high) * **[Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement](https://arxiv.org/abs/2506.20254v2)** - [Code](https://github.com/camma-public/spa) (confidence: medium) * **[Targeted False Positive Synthesis via Detector-guided Adversarial Diffusion Attacker for Robust Polyp Detection](https://arxiv.org/abs/2506.18134v1)** - [Code](https://github.com/huster-hq/dada) (confidence: high) * **[FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation](https://arxiv.org/abs/2506.04956v1)** - [Code](https://github.com/yaziwel/feat) (confidence: high) * **[Guiding Registration with Emergent Similarity from Pre-Trained Diffusion Models](https://arxiv.org/abs/2506.02419v1)** - [Code](https://github.com/uncbiag/dgir) (confidence: high) * **[Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays](https://arxiv.org/abs/2505.17311v1)** - [Code](https://github.com/nth221/diff3m) (confidence: high) * **[VesselGPT: Autoregressive Modeling of Vascular Geometry](https://arxiv.org/abs/2505.13318v2)** - [Code](https://github.com/lia-ditella/vesselgpt-miccai) (confidence: high) * **[Mission Balance: Generating Under-represented Class Samples using Video Diffusion Models](https://arxiv.org/abs/2505.09858v1)** - [Code](https://gitlab.com/nct_tso_public/surgvgen) (confidence: high) * **[Q-space Guided Collaborative Attention Translation Network for Flexible Diffusion-Weighted Images Synthesis](https://arxiv.org/abs/2505.09323v1)** - [Code](https://github.com/idea89560041/q-catn) (confidence: high) * **[Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models](https://arxiv.org/abs/2505.07001v2)** - [Code](https://github.com/bhattarailab/hallucination-aware-vlm) (confidence: medium) * **[DermDiff: Generative Diffusion Model for Mitigating Racial Biases in Dermatology Diagnosis](https://arxiv.org/abs/2503.17536v1)** - [Code](https://github.com/munia03/dermdiff) (confidence: high) * **[UniCrossAdapter: Multimodal Adaptation of CLIP for Radiology Report Generation](https://arxiv.org/abs/2503.15940v1)** - [Code](https://github.com/chauncey-tow/mrg-clip) (confidence: high) * **[Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models](https://arxiv.org/abs/2503.14966v1)** - [Code](https://github.com/medaitech/u_i2v) (confidence: high) * **[CyclePose -- Leveraging Cycle-Consistency for Annotation-Free Nuclei Segmentation in Fluorescence Microscopy](https://arxiv.org/abs/2503.11266v2)** - [Code](https://github.com/jonasutz/cyclepose) (confidence: high) * **[Prototype-Based Multiple Instance Learning for Gigapixel Whole Slide Image Classification](https://arxiv.org/abs/2503.08384v2)** - [Code](https://github.com/ss-sun/protomil) (confidence: medium) * **[Generating Novel Brain Morphology by Deforming Learned Templates](https://arxiv.org/abs/2503.03778v3)** - [Code](https://github.com/alanqrwang/morphldm) (confidence: high) * **[Surgical Vision World Model](https://arxiv.org/abs/2503.02904v2)** - [Code](https://github.com/bhattarailab/surgical-vision-world-model) (confidence: medium) * **[Conditional diffusion model with spatial attention and latent embedding for medical image segmentation](https://arxiv.org/abs/2502.06997v2)** - [Code](https://github.com/hejrati/cdal) (confidence: high) * **[RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment](https://arxiv.org/abs/2501.07525v2)** - [Code](https://github.com/difeigu/radalign) (confidence: high) * **[Predicting Human Brain States with Transformer](https://arxiv.org/abs/2412.19814v1)** - [Code](https://github.com/syf0122/brain_state_pred) (confidence: medium) * **[Improving Factuality of 3D Brain MRI Report Generation with Paired Image-domain Retrieval and Text-domain Augmentation](https://arxiv.org/abs/2411.15490v3)** - [Code](https://github.com/jhlee0619/pirta) (confidence: high) * **[SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation](https://arxiv.org/abs/2411.12602v1)** - [Code](https://github.com/multimodallearning/samcarriestheburden) (confidence: medium) * **[DiffuseReg: Denoising Diffusion Model for Obtaining Deformation Fields in Unsupervised Deformable Image Registration](https://arxiv.org/abs/2410.05234v1)** - [Code](https://github.com/yutazhuo/diffusereg) (confidence: high) * **[Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2409.12522v1)** - [Code](https://github.com/wkklavis/dapsam) (confidence: medium) * **[Estimating Neural Orientation Distribution Fields on High Resolution Diffusion MRI Scans](https://arxiv.org/abs/2409.09387v1)** - [Code](https://github.com/munzerdw/nodf-hashenc) (confidence: high) * **[Intrapartum Ultrasound Image Segmentation of Pubic Symphysis and Fetal Head Using Dual Student-Teacher Framework with CNN-ViT Collaborative Learning](https://arxiv.org/abs/2409.06928v1)** - [Code](https://github.com/jjm1589/dstct) (confidence: medium) * **[Spatial Diffusion for Cell Layout Generation](https://arxiv.org/abs/2409.03106v1)** - [Code](https://github.com/superlc1995/diffusion-cell) (confidence: high) * **[Curriculum Prompting Foundation Models for Medical Image Segmentation](https://arxiv.org/abs/2409.00695v1)** - [Code](https://github.com/annazzz-zxq/curriculum-prompting) (confidence: medium) * **[Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance](https://arxiv.org/abs/2408.15217v1)** - [Code](https://github.com/michi-3000/fundus2video) (confidence: high) * **[HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training](https://arxiv.org/abs/2408.05815v1)** - [Code](https://github.com/fenghetan9/hyspark) (confidence: medium) * **[Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis](https://arxiv.org/abs/2408.03035v2)** - [Code](https://github.com/gungui98/echo-free) (confidence: high) * **[AMAES: Augmented Masked Autoencoder Pretraining on Public Brain MRI Data for 3D-Native Segmentation](https://arxiv.org/abs/2408.00640v2)** - [Code](https://github.com/asbjrnmunk/amaes) (confidence: high) * **[Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation](https://arxiv.org/abs/2407.21490v1)** - [Code](https://github.com/mlmi-2024-72/ecm) (confidence: high) * **[Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations](https://arxiv.org/abs/2407.20072v1)** - [Code](https://github.com/13204942/fu-lora) (confidence: high) * **[Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation](https://arxiv.org/abs/2407.19284v2)** - [Code](https://github.com/lkpengcs/syntumoranalyzer) (confidence: high) * **[Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data](https://arxiv.org/abs/2407.12669v1)** - [Code](https://github.com/richardobi/mammo_dp) (confidence: medium) * **[DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation](https://arxiv.org/abs/2407.09918v1)** - [Code](https://github.com/cuhk-aim-group/diffrect) (confidence: high) * **[Region Attention Transformer for Medical Image Restoration](https://arxiv.org/abs/2407.09268v1)** - [Code](https://github.com/yaziwel/region-attention-transformer-for-medical-image-restoration) (confidence: medium) * **[FairDiff: Fair Segmentation with Point-Image Diffusion](https://arxiv.org/abs/2407.06250v1)** - [Code](https://github.com/wenyi-li/fairdiff) (confidence: high) * **[RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features](https://arxiv.org/abs/2407.05683v2)** - [Code](https://github.com/nainye/radiomicsfill) (confidence: high) * **[An Organism Starts with a Single Pix-Cell: A Neural Cellular Diffusion for High-Resolution Image Synthesis](https://arxiv.org/abs/2407.03018v1)** - [Code](https://github.com/xmed-lab/geca) (confidence: high) * **[Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction](https://arxiv.org/abs/2407.02918v1)** - [Code](https://github.com/wrld/free-surgs) (confidence: medium) * **[Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization](https://arxiv.org/abs/2407.02900v1)** - [Code](https://github.com/sdoerrich97/vits-are-generative-models) (confidence: high) * **[Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis](https://arxiv.org/abs/2406.18967v2)** - [Code](https://github.com/hieuphan33/miccai2024-unest) (confidence: high) * **[Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process](https://arxiv.org/abs/2406.18361v3)** - [Code](https://github.com/lin-tianyu/stable-diffusion-seg) (confidence: high) * **[Scalp Diagnostic System With Label-Free Segmentation and Training-Free Image Translation](https://arxiv.org/abs/2406.17254v3)** - [Code](https://github.com/winston1214/scalpvision) (confidence: medium) * **[DiffExplainer: Unveiling Black Box Models Via Counterfactual Generation](https://arxiv.org/abs/2406.15182v2)** - [Code](https://github.com/ayanglab/diffexplainer) (confidence: high) * **[Groupwise Deformable Registration of Diffusion Tensor Cardiovascular Magnetic Resonance: Disentangling Diffusion Contrast, Respiratory and Cardiac Motions](https://arxiv.org/abs/2406.13788v2)** - [Code](https://github.com/ayanglab/dtcmr-reg) (confidence: high) * **[EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy](https://arxiv.org/abs/2406.13705v2)** - [Code](https://github.com/longbai1006/endouic) (confidence: high) * **[EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data Sharing](https://arxiv.org/abs/2406.00808v1)** - [Code](https://github.com/hreynaud/echonet-synthetic) (confidence: high) * **[All-In-One Medical Image Restoration via Task-Adaptive Routing](https://arxiv.org/abs/2405.19769v2)** - [Code](https://github.com/yaziwel/all-in-one-medical-image-restoration-via-task-adaptive-routing) (confidence: medium) * **[EgoSurgery-Phase: A Dataset of Surgical Phase Recognition from Egocentric Open Surgery Videos](https://arxiv.org/abs/2405.19644v3)** - [Code](https://github.com/fujiry0/egosurgery) (confidence: medium) * **[Memory-efficient High-resolution OCT Volume Synthesis with Cascaded Amortized Latent Diffusion Models](https://arxiv.org/abs/2405.16516v1)** - [Code](https://github.com/nicetomeetu21/ca-ldm) (confidence: high) * **[Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation](https://arxiv.org/abs/2405.16102v1)** - [Code](https://github.com/zenghy96/reliable-source-approximation) (confidence: medium) * **[Position-Guided Prompt Learning for Anomaly Detection in Chest X-Rays](https://arxiv.org/abs/2405.11976v2)** - [Code](https://github.com/sunzc-sunny/ppad) (confidence: medium) * **[MediCLIP: Adapting CLIP for Few-shot Medical Image Anomaly Detection](https://arxiv.org/abs/2405.11315v1)** - [Code](https://github.com/cnulab/mediclip) (confidence: medium) * **[Eddeep: Fast eddy-current distortion correction for diffusion MRI with deep learning](https://arxiv.org/abs/2405.10723v3)** - [Code](https://github.com/cig-ucl/eddeep) (confidence: high) * **[MMFusion: Multi-modality Diffusion Model for Lymph Node Metastasis Diagnosis in Esophageal Cancer](https://arxiv.org/abs/2405.09539v2)** - [Code](https://github.com/wuchengyu123/mmfusion) (confidence: high) * **[Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion Model](https://arxiv.org/abs/2404.17357v4)** - [Code](https://github.com/xylonxu01/tfs-diff) (confidence: high) * **[Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks](https://arxiv.org/abs/2403.19880v1)** - [Code](https://github.com/pooria90/diffecho) (confidence: high) * **[MEDDAP: Medical Dataset Enhancement via Diversified Augmentation Pipeline](https://arxiv.org/abs/2403.16335v2)** - [Code](https://github.com/yasamin-med/meddap) (confidence: high) * **[Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor Segmentation](https://arxiv.org/abs/2403.09942v1)** - [Code](https://github.com/yaziciz/glims) (confidence: medium) * **[Counterfactual contrastive learning: robust representations via causal image synthesis](https://arxiv.org/abs/2403.09605v3)** - [Code](https://github.com/biomedia-mira/counterfactual-contrastive) (confidence: high) * **[$TrIND$: Representing Anatomical Trees by Denoising Diffusion of Implicit Neural Fields](https://arxiv.org/abs/2403.08974v3)** - [Code](https://github.com/sinashish/treediffusion) (confidence: high) * **[From Pixel to Cancer: Cellular Automata in Computed Tomography](https://arxiv.org/abs/2403.06459v2)** - [Code](https://github.com/mrgiovanni/pixel2cancer) (confidence: medium) * **[Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models](https://arxiv.org/abs/2402.05210v4)** - [Code](https://github.com/mazurowski-lab/segmentation-guided-diffusion) (confidence: high) * **[VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification](https://arxiv.org/abs/2402.01034v3)** - [Code](https://github.com/lzl199704/vis-mae) (confidence: medium) * **[DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Models](https://arxiv.org/abs/2312.04853v1)** - [Code](https://github.com/xmed-lab/diffcmr) (confidence: high) * **[Diffusion-based Data Augmentation for Nuclei Image Segmentation](https://arxiv.org/abs/2310.14197v2)** - [Code](https://github.com/lhaof/nudiff) (confidence: high) * **[Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration](https://arxiv.org/abs/2310.11040v3)** - [Code](https://github.com/brain-intelligence-lab/girnet) (confidence: medium) * **[SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models](https://arxiv.org/abs/2310.01799v2)** - [Code](https://github.com/nvlabs/smrd) (confidence: high) * **[RT-GAN: Recurrent Temporal GAN for Adding Lightweight Temporal Consistency to Frame-Based Domain Translation Approaches](https://arxiv.org/abs/2310.00868v2)** - [Code](https://github.com/nadeemlab/cep) (confidence: high) * **[Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations](https://arxiv.org/abs/2309.08747v2)** - [Code](https://github.com/reubendo/mhvae) (confidence: high) * **[Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning](https://arxiv.org/abs/2309.03440v1)** - [Code](https://github.com/ladderlab-xjtu/deeppwml) (confidence: high) * **[TAI-GAN: Temporally and Anatomically Informed GAN for early-to-late frame conversion in dynamic cardiac PET motion correction](https://arxiv.org/abs/2308.12443v1)** - [Code](https://github.com/gxq1998/tai-gan) (confidence: high) * **[Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction](https://arxiv.org/abs/2308.10157v1)** - [Code](https://github.com/show-han/pet-reconstruction) (confidence: high) * **[DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction](https://arxiv.org/abs/2308.09223v1)** - [Code](https://github.com/hexiaoxiao-cs/dmcvr) (confidence: high) * **[Synthetic Augmentation with Large-scale Unconditional Pre-training](https://arxiv.org/abs/2308.04020v1)** - [Code](https://github.com/karenyyy/histodiffaug) (confidence: high) * **[DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation](https://arxiv.org/abs/2308.02959v1)** - [Code](https://github.com/mindflow-institue/dermosegdiff) (confidence: high) * **[Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection](https://arxiv.org/abs/2308.01639v1)** - [Code](https://github.com/mediabrain-sjtu/ecgad) (confidence: medium) * **[Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation](https://arxiv.org/abs/2307.16143v2)** - [Code](https://github.com/hieuphan33/maskgan) (confidence: high) * **[FSDiffReg: Feature-wise and Score-wise Diffusion-guided Unsupervised Deformable Image Registration for Cardiac Images](https://arxiv.org/abs/2307.12035v1)** - [Code](https://github.com/xmed-lab/fsdiffreg) (confidence: high) * **[Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation](https://arxiv.org/abs/2307.11604v1)** - [Code](https://github.com/aijinrjinr/mlb-seg) (confidence: medium) * **[DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image Synthesis](https://arxiv.org/abs/2307.05249v1)** - [Code](https://github.com/yaziwel/multi-center-pet-image-synthesis) (confidence: high) * **[Unsupervised 3D out-of-distribution detection with latent diffusion models](https://arxiv.org/abs/2307.03777v1)** - [Code](https://github.com/marksgraham/ddpm-ood) (confidence: high) * **[LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion](https://arxiv.org/abs/2307.02452v2)** - [Code](https://github.com/longbai1006/llcaps) (confidence: high) * **[Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks](https://arxiv.org/abs/2307.00899v1)** - [Code](https://github.com/matt-baugh/many-tasks-make-light-work) (confidence: medium) * **[Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism](https://arxiv.org/abs/2307.00895v1)** - [Code](https://github.com/netherlands-cancer-institute/ce-mri) (confidence: high) * **[Beyond the Snapshot: Brain Tokenized Graph Transformer for Longitudinal Brain Functional Connectome Embedding](https://arxiv.org/abs/2307.00858v2)** - [Code](https://github.com/zijiand/brain-tokengt) (confidence: medium) * **[Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train](https://arxiv.org/abs/2306.16741v4)** - [Code](https://github.com/med-air/endo-fm) (confidence: medium) * **[CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?](https://arxiv.org/abs/2306.14350v1)** - [Code](https://github.com/ayanglab/cdiffmr) (confidence: high) * **[Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset](https://arxiv.org/abs/2306.07089v2)** - [Code](https://github.com/m3dv/pulmonary-tree-repairing) (confidence: medium) * **[DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation](https://arxiv.org/abs/2306.00499v2)** - [Code](https://github.com/yifangao112/desam) (confidence: medium) * **[Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model](https://arxiv.org/abs/2305.19867v2)** - [Code](https://github.com/hasan1292/mddpm) (confidence: high) * **[DENTEX: Dental Enumeration and Tooth Pathosis Detection Benchmark for Panoramic X-ray](https://arxiv.org/abs/2305.19112v2)** - [Code](https://github.com/ibrahimethemhamamci/dentex) (confidence: medium) * **[Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery](https://arxiv.org/abs/2305.11692v1)** - [Code](https://github.com/longbai1006/surgical-vqla) (confidence: medium) * **[DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models](https://arxiv.org/abs/2304.13416v2)** - [Code](https://github.com/shaoshitong/diffuseexpand) (confidence: high) * **[Cross-modulated Few-shot Image Generation for Colorectal Tissue Classification](https://arxiv.org/abs/2304.01992v2)** - [Code](https://github.com/virobo-15/xm-gan) (confidence: high) * **[Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis](https://arxiv.org/abs/2303.12644v3)** - [Code](https://github.com/hreynaud/echodiffusion) (confidence: high) * **[Point Cloud Diffusion Models for Automatic Implant Generation](https://arxiv.org/abs/2303.08061v2)** - [Code](https://github.com/pfriedri/pcdiff-implant) (confidence: high) * **[Learning Deep Intensity Field for Extremely Sparse-View CBCT Reconstruction](https://arxiv.org/abs/2303.06681v3)** - [Code](https://github.com/xmed-lab/dif-net) (confidence: medium) * **[Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays](https://arxiv.org/abs/2303.06500v3)** - [Code](https://github.com/ibrahimethemhamamci/hierarchicaldet) (confidence: high) * **[Importance of Aligning Training Strategy with Evaluation for Diffusion Models in 3D Multiclass Segmentation](https://arxiv.org/abs/2303.06040v3)** - [Code](https://github.com/mathpluscode/imgx-diffseg) (confidence: high) * **[Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine Learning](https://arxiv.org/abs/2210.02349v1)** - [Code](https://github.com/jplte/deep-t1-ball-stick) (confidence: high) * **[Reducing Positional Variance in Cross-sectional Abdominal CT Slices with Deep Conditional Generative Models](https://arxiv.org/abs/2209.14467v1)** - [Code](https://github.com/masilab/c-slicegen) (confidence: high) * **[Attentive Symmetric Autoencoder for Brain MRI Segmentation](https://arxiv.org/abs/2209.08887v1)** - [Code](https://github.com/lhaof/asa) (confidence: high) * **[Landmark-free Statistical Shape Modeling via Neural Flow Deformations](https://arxiv.org/abs/2209.06861v1)** - [Code](https://github.com/davecasp/flowssm) (confidence: medium) * **[Morphology-preserving Autoregressive 3D Generative Modelling of the Brain](https://arxiv.org/abs/2209.03177v1)** - [Code](https://github.com/amigolab/synthanatomy) (confidence: high) * **[Airway measurement by refinement of synthetic images improves mortality prediction in idiopathic pulmonary fibrosis](https://arxiv.org/abs/2208.14141v1)** - [Code](https://github.com/ashkanpakzad/atn) (confidence: high) * **[Fast Auto-Differentiable Digitally Reconstructed Radiographs for Solving Inverse Problems in Intraoperative Imaging](https://arxiv.org/abs/2208.12737v1)** - [Code](https://github.com/v715/diffdrr) (confidence: high) * **[Unsupervised Anomaly Localization with Structural Feature-Autoencoders](https://arxiv.org/abs/2208.10992v1)** - [Code](https://github.com/felime/feature-autoencoder) (confidence: medium) * **[Seamless Iterative Semi-Supervised Correction of Imperfect Labels in Microscopy Images](https://arxiv.org/abs/2208.03327v1)** - [Code](https://github.com/marwankefah/sissi) (confidence: medium) * **[Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN](https://arxiv.org/abs/2208.03008v1)** - [Code](https://github.com/yongsongh/aidsrgan-miccai2022) (confidence: medium) * **[Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images](https://arxiv.org/abs/2208.02135v1)** - [Code](https://github.com/dogabasaran/lesion-synthesis) (confidence: high) * **[What is Healthy? Generative Counterfactual Diffusion for Lesion Localization](https://arxiv.org/abs/2207.12268v1)** - [Code](https://github.com/vios-s/diff-scm) (confidence: high) * **[Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approach](https://arxiv.org/abs/2207.00844v1)** - [Code](https://github.com/winstonhutiger/2d_vae_uda_for_3d_sythesis) (confidence: high) * **[CLTS-GAN: Color-Lighting-Texture-Specular Reflection Augmentation for Colonoscopy](https://arxiv.org/abs/2206.14951v1)** - [Code](https://github.com/nadeemlab/cep) (confidence: high) * **[D'ARTAGNAN: Counterfactual Video Generation](https://arxiv.org/abs/2206.01651v2)** - [Code](https://github.com/hreynaud/dartagnan) (confidence: high) * **[Progressive Subsampling for Oversampled Data - Application to Quantitative MRI](https://arxiv.org/abs/2203.09268v5)** - [Code](https://github.com/sbb-gh/prosub) (confidence: medium) * **[CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data](https://arxiv.org/abs/2203.09475v3)** - [Code](https://github.com/hding2455/carts) (confidence: medium) * **[Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs](https://arxiv.org/abs/2201.07344v1)** - [Code](https://github.com/cvlab-stonybrook/lsae) (confidence: high) * **[Virtual Reality for Synergistic Surgical Training and Data Generation](https://arxiv.org/abs/2111.08097v1)** - [Code](https://github.com/lcsr-sickkids/volumetric_drilling) (confidence: high) * **[A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis](https://arxiv.org/abs/2111.06398v1)** - [Code](https://github.com/karenyyy/miccai2021attributegan) (confidence: high) * **[RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans](https://arxiv.org/abs/2109.09521v1)** - [Code](https://github.com/m3dv/ribseg) (confidence: medium) * **[Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation](https://arxiv.org/abs/2108.05269v1)** - [Code](https://github.com/jianningli/voxel_rearrangement) (confidence: medium) * **[Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations](https://arxiv.org/abs/2107.12357v1)** - [Code](https://github.com/sophiajw/histaugan) (confidence: high) * **[Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation](https://arxiv.org/abs/2107.11091v1)** - [Code](https://github.com/xumengyaamy/cidacaptioning) (confidence: high) * **[Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations](https://arxiv.org/abs/2107.10839v1)** - [Code](https://github.com/fkong7/heartffdnet) (confidence: high) * **[3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images](https://arxiv.org/abs/2107.09700v1)** - [Code](https://github.com/sh4174/3dstylegan) (confidence: high) * **[Frequency-Supervised MR-to-CT Image Synthesis](https://arxiv.org/abs/2107.08962v1)** - [Code](https://github.com/shizenglin/frequency-supervised-mr-to-ct-image-synthesis) (confidence: high) * **[Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation](https://arxiv.org/abs/2107.06941v2)** - [Code](https://github.com/cardio-ai/detcyclegan_pytorch) (confidence: high) * **[Controllable cardiac synthesis via disentangled anatomy arithmetic](https://arxiv.org/abs/2107.01748v1)** - [Code](https://github.com/vios-s/daa-gan) (confidence: high) * **[Uncertainty-Guided Progressive GANs for Medical Image Translation](https://arxiv.org/abs/2106.15542v2)** - [Code](https://github.com/explainableml/uncerguidedi2i) (confidence: high) * **[Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI](https://arxiv.org/abs/2106.13188v1)** - [Code](https://github.com/mengweiren/q-space-conditioned-dwi-synthesis) (confidence: high) * **[FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos](https://arxiv.org/abs/2106.12522v2)** - [Code](https://github.com/nadeemlab/cep) (confidence: medium) * **[TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation](https://arxiv.org/abs/2105.08993v1)** - [Code](https://github.com/2165998/targan) (confidence: high) * **[Predictive Modeling of Anatomy with Genetic and Clinical Data](https://arxiv.org/abs/2010.04757v1)** - [Code](https://github.com/adalca/voxelorb) (confidence: medium) * **[Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE](https://arxiv.org/abs/2007.04780v1)** - [Code](https://github.com/voanna/slices-to-3d-brain-vae) (confidence: high) * **[MvMM-RegNet: A new image registration framework based on multivariate mixture model and neural network estimation](https://arxiv.org/abs/2006.15573v2)** - [Code](https://github.com/xzluo97/mvmm-regnet) (confidence: medium) * **[Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation](https://arxiv.org/abs/1910.04961v2)** - [Code](https://github.com/yunyanxing/pairwise_xray_augmentation) (confidence: high) * **[Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest x-rays](https://arxiv.org/abs/1908.10468v1)** - [Code](https://github.com/ricbl/vrgan) (confidence: high) * **[Disease Knowledge Transfer across Neurodegenerative Diseases](https://arxiv.org/abs/1901.03517v2)** - [Code](https://github.com/mrazvan22/dkt) (confidence: medium) ## 📚 General *This list is automatically generated. See any issues? Please open a pull request!* * **[ENC-ODE: Event-level Neurodegenerative Modeling in Continuous Time with Neural ODEs](https://arxiv.org/abs/2606.30398v1)** - [Code](https://github.com/jardindelsol/enc-ode) (confidence: medium) * **[Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning](https://arxiv.org/abs/2606.25770v1)** - [Code](https://github.com/marrlab/recipe) (confidence: medium) * **[AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction](https://arxiv.org/abs/2606.12126v1)** - [Code](https://github.com/wodeniua/age-mil) (confidence: medium) * **[StrokeTimer: Robust Representation Learning for Ischemic Stroke Onset-Time Estimation from Non-contrast CT](https://arxiv.org/abs/2606.04722v1)** - [Code](https://github.com/brainvas/stroketimer) (confidence: medium) * **[BCER Agent: Reliable Long-Horizon MRI Workflow Execution via Compilation, Artifact Binding, and Bounded Local Recovery](https://arxiv.org/abs/2605.29163v1)** - [Code](https://github.com/albertlongzi/bcer) (confidence: medium) * **[BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma](https://arxiv.org/abs/2605.26376v1)** - [Code](https://github.com/jy-639/biofact-moe) (confidence: medium) * **[SurgLQA: Scalable Long-Horizon Surgical Video Question Answering](https://arxiv.org/abs/2605.17915v1)** - [Code](https://github.com/rascalgdd/surglqa) (confidence: medium) * **[Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning](https://arxiv.org/abs/2605.14048v3)** - [Code](https://github.com/leomlck/nerve) (confidence: medium) * **[Clinical Graph-Mediated Distillation for Unpaired MRI-to-CFI Hypertension Prediction](https://arxiv.org/abs/2603.21809v1)** - [Code](https://github.com/dillanimans/cgmd-unpaired-distillation) (confidence: medium) * **[FusionNet: a frame interpolation network for 4D heart models](https://arxiv.org/abs/2603.10212v1)** - [Code](https://github.com/smiyauchi199/fusionnet) (confidence: medium) * **[UltraStar: Semantic-Aware Star Graph Modeling for Echocardiography Navigation](https://arxiv.org/abs/2603.01461v2)** - [Code](https://github.com/leaplabthu/ultrastar) (confidence: medium) * **[Can Agents Distinguish Visually Hard-to-Separate Diseases in a Zero-Shot Setting? A Pilot Study](https://arxiv.org/abs/2602.22959v2)** - [Code](https://github.com/truhnlab/contrastive-agent-reasoning) (confidence: medium) * **[From 100,000+ images to winning the first brain MRI foundation model challenges: Sharing lessons and models](https://arxiv.org/abs/2601.13166v1)** - [Code](https://github.com/jbanusco/brainfm4challenges) (confidence: medium) * **[ProtoEFNet: Dynamic Prototype Learning for Inherently Interpretable Ejection Fraction Estimation in Echocardiography](https://arxiv.org/abs/2512.03339v1)** - [Code](https://github.com/deeprcl/protoef) (confidence: medium) * **[Augment to Augment: Diverse Augmentations Enable Competitive Ultra-Low-Field MRI Enhancement](https://arxiv.org/abs/2511.09366v1)** - [Code](https://github.com/fzimmermann89/low-field-enhancement) (confidence: medium) * **[MedPAO: A Protocol-Driven Agent for Structuring Medical Reports](https://arxiv.org/abs/2510.04623v1)** - [Code](https://github.com/mirl-iitm/medpao-agent) (confidence: medium) * **[EchoingECG: An Electrocardiogram Cross-Modal Model for Echocardiogram Tasks](https://arxiv.org/abs/2509.25791v1)** - [Code](https://github.com/mcintoshml/echoingecg) (confidence: medium) * **[Evaluating Foundation Models with Pathological Concept Learning for Kidney Cancer](https://arxiv.org/abs/2509.25552v1)** - [Code](https://github.com/shangqigao/radiopath) (confidence: medium) * **[CardiacCLIP: Video-based CLIP Adaptation for LVEF Prediction in a Few-shot Manner](https://arxiv.org/abs/2509.17065v1)** - [Code](https://github.com/xmed-lab/cardiacclip) (confidence: medium) * **[Exploring Pre-training Across Domains for Few-Shot Surgical Skill Assessment](https://arxiv.org/abs/2509.09327v1)** - [Code](https://github.com/anastadimi/ssa-fsl) (confidence: medium) * **[Implicit Neural Representations of Intramyocardial Motion and Strain](https://arxiv.org/abs/2509.09004v4)** - [Code](https://github.com/andrewjackbell/displacement-inr) (confidence: medium) * **[Multi-modal Knowledge Decomposition based Online Distillation for Biomarker Prediction in Breast Cancer Histopathology](https://arxiv.org/abs/2508.17213v1)** - [Code](https://github.com/qiyuanzz/miccai2025_mkd) (confidence: medium) * **[FIND-Net -- Fourier-Integrated Network with Dictionary Kernels for Metal Artifact Reduction](https://arxiv.org/abs/2508.10617v1)** - [Code](https://github.com/farid-tasharofi/find-net) (confidence: medium) * **[From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations](https://arxiv.org/abs/2508.09205v2)** - [Code](https://github.com/nki-ai/x2x) (confidence: medium) * **[Analysis of Image-and-Text Uncertainty Propagation in Multimodal Large Language Models with Cardiac MR-Based Applications](https://arxiv.org/abs/2507.12945v1)** - [Code](https://github.com/yucheng722/mupm) (confidence: medium) * **[Trexplorer Super: Topologically Correct Centerline Tree Tracking of Tubular Objects in CT Volumes](https://arxiv.org/abs/2507.10881v1)** - [Code](https://github.com/romstriker/trexplorer-super) (confidence: medium) * **[Temporally-Aware Supervised Contrastive Learning for Polyp Counting in Colonoscopy](https://arxiv.org/abs/2507.02493v1)** - [Code](https://github.com/lparolari/temporally-aware-polyp-counting) (confidence: medium) * **[Accurate and Efficient Fetal Birth Weight Estimation from 3D Ultrasound](https://arxiv.org/abs/2507.00398v1)** - [Code](https://github.com/qioy-i/efw) (confidence: medium) * **[Spatially Gene Expression Prediction using Dual-Scale Contrastive Learning](https://arxiv.org/abs/2506.23827v1)** - [Code](https://github.com/mcpathology/nh2st) (confidence: medium) * **[OTSurv: A Novel Multiple Instance Learning Framework for Survival Prediction with Heterogeneity-aware Optimal Transport](https://arxiv.org/abs/2506.20741v2)** - [Code](https://github.com/y-research-sbu/otsurv) (confidence: medium) * **[Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images](https://arxiv.org/abs/2506.20407v2)** - [Code](https://github.com/13204942/radiomicsimagefusion_fetalus) (confidence: medium) * **[MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment](https://arxiv.org/abs/2506.20200v1)** - [Code](https://github.com/ms-iqa/ms-iqa) (confidence: medium) * **[MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis](https://arxiv.org/abs/2506.18028v3)** - [Code](https://github.com/junjianli106/mico) (confidence: medium) * **[Few-Shot, Now for Real: Medical VLMs Adaptation without Balanced Sets or Validation](https://arxiv.org/abs/2506.17500v1)** - [Code](https://github.com/jusiro/ss-text) (confidence: medium) * **[MrTrack: Register Mamba for Needle Tracking with Rapid Reciprocating Motion during Ultrasound-Guided Aspiration Biopsy](https://arxiv.org/abs/2505.09450v2)** - [Code](https://github.com/piecezhang/mrtrack) (confidence: medium) * **[BrainPrompt: Multi-Level Brain Prompt Enhancement for Neurological Condition Identification](https://arxiv.org/abs/2504.16096v2)** - [Code](https://github.com/angusmonroe/brainprompt) (confidence: medium) * **[Rethinking Cell Counting Methods: Decoupling Counting and Localization](https://arxiv.org/abs/2503.13989v1)** - [Code](https://github.com/medaitech/dcl) (confidence: medium) * **[Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology](https://arxiv.org/abs/2503.10629v2)** - [Code](https://github.com/hashmatshadab/hsat) (confidence: medium) * **[GAMMA-PD: Graph-based Analysis of Multi-Modal Motor Impairment Assessments in Parkinson's Disease](https://arxiv.org/abs/2410.00944v1)** - [Code](https://github.com/favour-nerrise/gamma-pd) (confidence: medium) * **[Topological SLAM in colonoscopies leveraging deep features and topological priors](https://arxiv.org/abs/2409.16806v1)** - [Code](https://github.com/endomapper/colonslam) (confidence: medium) * **[Benchmarking Robustness of Endoscopic Depth Estimation with Synthetically Corrupted Data](https://arxiv.org/abs/2409.16063v1)** - [Code](https://github.com/lofrienger/endodepthbenchmark) (confidence: medium) * **[TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing](https://arxiv.org/abs/2409.07564v1)** - [Code](https://github.com/sanoscience/tabmixer) (confidence: medium) * **[Few-shot Adaptation of Medical Vision-Language Models](https://arxiv.org/abs/2409.03868v1)** - [Code](https://github.com/fereshteshakeri/few-shot-medvlms) (confidence: medium) * **[Multi-task Learning Approach for Intracranial Hemorrhage Prognosis](https://arxiv.org/abs/2408.08784v2)** - [Code](https://github.com/miriamcobo/multitasklearning_ich_prognosis) (confidence: medium) * **[Targeted Visual Prompting for Medical Visual Question Answering](https://arxiv.org/abs/2408.03043v1)** - [Code](https://github.com/sergiotasconmorales/locvqallm) (confidence: medium) * **[Advancing Brain Imaging Analysis Step-by-step via Progressive Self-paced Learning](https://arxiv.org/abs/2407.16128v1)** - [Code](https://github.com/hrychen7/pspd) (confidence: medium) * **[TaGAT: Topology-Aware Graph Attention Network For Multi-modal Retinal Image Fusion](https://arxiv.org/abs/2407.14188v1)** - [Code](https://github.com/xintian-99/tagat) (confidence: medium) * **[FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging](https://arxiv.org/abs/2407.08822v1)** - [Code](https://github.com/m1k2zoo/fedmedicl) (confidence: medium) * **[CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities](https://arxiv.org/abs/2407.08648v1)** - [Code](https://github.com/bhattarailab/car-mfl) (confidence: medium) * **[FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging](https://arxiv.org/abs/2407.05800v1)** - [Code](https://github.com/pranabiitp/fedmrl) (confidence: medium) * **[MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise](https://arxiv.org/abs/2405.11793v1)** - [Code](https://github.com/lxirich/mm-retinal) (confidence: medium) * **[Rethinking Histology Slide Digitization Workflows for Low-Resource Settings](https://arxiv.org/abs/2405.08169v1)** - [Code](https://github.com/nadeemlab/deepliif) (confidence: medium) * **[PathoTune: Adapting Visual Foundation Model to Pathological Specialists](https://arxiv.org/abs/2403.16497v2)** - [Code](https://github.com/openmedlab/pathoduet) (confidence: medium) * **[MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology](https://arxiv.org/abs/2403.06800v1)** - [Code](https://github.com/isyangshu/mambamil) (confidence: medium) * **[Adjustable Robust Transformer for High Myopia Screening in Optical Coherence Tomography](https://arxiv.org/abs/2312.07052v1)** - [Code](https://github.com/maxiao0234/artran) (confidence: medium) * **[TabAttention: Learning Attention Conditionally on Tabular Data](https://arxiv.org/abs/2310.18129v1)** - [Code](https://github.com/sanoscience/tab-attention) (confidence: medium) * **[Autonomous Soft Tissue Retraction Using Demonstration-Guided Reinforcement Learning](https://arxiv.org/abs/2309.00837v1)** - [Code](https://github.com/amritpal-001/tissue_retract) (confidence: medium) * **[Pose2Gait: Extracting Gait Features from Monocular Video of Individuals with Dementia](https://arxiv.org/abs/2308.11484v1)** - [Code](https://github.com/taatiteam/pose2gait_public) (confidence: medium) * **[Centroid-aware feature recalibration for cancer grading in pathology images](https://arxiv.org/abs/2307.13947v1)** - [Code](https://github.com/colin19950703/cafenet) (confidence: medium) * **[An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment](https://arxiv.org/abs/2307.13108v1)** - [Code](https://github.com/favour-nerrise/xgw-gat) (confidence: medium) * **[Multi-View Vertebra Localization and Identification from CT Images](https://arxiv.org/abs/2307.12845v1)** - [Code](https://github.com/shanghaitech-impact/multi-view-vertebra-localization-and-identification-from-ct-images) (confidence: medium) * **[Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery](https://arxiv.org/abs/2307.12045v1)** - [Code](https://github.com/longbai1006/cs-vqla) (confidence: medium) * **[SLPD: Slide-level Prototypical Distillation for WSIs](https://arxiv.org/abs/2307.10696v1)** - [Code](https://github.com/carboxy/slpd) (confidence: medium) * **[Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting](https://arxiv.org/abs/2307.05766v4)** - [Code](https://github.com/chantalmp/rad-restruct) (confidence: medium) * **[Localized Questions in Medical Visual Question Answering](https://arxiv.org/abs/2307.01067v1)** - [Code](https://github.com/sergiotasconmorales/locvqa) (confidence: medium) * **[Community-Aware Transformer for Autism Prediction in fMRI Connectome](https://arxiv.org/abs/2307.10181v1)** - [Code](https://github.com/ubc-tea/com-braintf) (confidence: medium) * **[An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment](https://arxiv.org/abs/2305.16465v1)** - [Code](https://github.com/nadeemlab/deepliif) (confidence: medium) * **[SlicerTMS: Real-Time Visualization of Transcranial Magnetic Stimulation for Mental Health Treatment](https://arxiv.org/abs/2305.06459v4)** - [Code](https://github.com/lorifranke/slicertms) (confidence: medium) * **[Operating critical machine learning models in resource constrained regimes](https://arxiv.org/abs/2303.10181v2)** - [Code](https://github.com/raghavian/redl) (confidence: medium) * **[Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images](https://arxiv.org/abs/2209.05477v1)** - [Code](https://github.com/pakheiyeung/adlocui) (confidence: medium) * **[A Benchmark for Weakly Semi-Supervised Abnormality Localization in Chest X-Rays](https://arxiv.org/abs/2209.01988v1)** - [Code](https://github.com/haozheliu-st/point-beyond-class) (confidence: medium) * **[INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical Examples](https://arxiv.org/abs/2208.00457v1)** - [Code](https://github.com/lindehesse/insightr-net) (confidence: medium) * **[The Intrinsic Manifolds of Radiological Images and their Role in Deep Learning](https://arxiv.org/abs/2207.02797v1)** - [Code](https://github.com/mazurowski-lab/radiologyintrinsicmanifolds) (confidence: medium) * **[GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation](https://arxiv.org/abs/2207.00106v1)** - [Code](https://github.com/markendo/gaitforemer) (confidence: medium) * **[Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis](https://arxiv.org/abs/2207.00813v2)** - [Code](https://github.com/hennyjie/ibgnn) (confidence: medium) * **[Consistency-preserving Visual Question Answering in Medical Imaging](https://arxiv.org/abs/2206.13296v1)** - [Code](https://github.com/sergiotasconmorales/consistency_vqa) (confidence: medium) * **[Multiple Instance Learning with Mixed Supervision in Gleason Grading](https://arxiv.org/abs/2206.12798v1)** - [Code](https://github.com/bianhao123/mixed_supervision) (confidence: medium) * **[ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment](https://arxiv.org/abs/2206.06623v1)** - [Code](https://github.com/perceptioncomputinglab/ultra) (confidence: medium) * **[FedHarmony: Unlearning Scanner Bias with Distributed Data](https://arxiv.org/abs/2205.15970v1)** - [Code](https://github.com/nkdinsdale/fedharmony) (confidence: medium) * **[BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video](https://arxiv.org/abs/2205.09382v2)** - [Code](https://github.com/sanoscience/babynet) (confidence: medium) * **[AdaTriplet: Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching](https://arxiv.org/abs/2205.02849v2)** - [Code](https://github.com/oulu-imeds/adatriplet) (confidence: medium) * **[A Real-Time Region Tracking Algorithm Tailored to Endoscopic Video with Open-Source Implementation](https://arxiv.org/abs/2203.08858v1)** - [Code](https://github.com/ibm/optflow-region-tracker) (confidence: medium) * **[Volumetric Parameterization of the Placenta to a Flattened Template](https://arxiv.org/abs/2111.07900v1)** - [Code](https://github.com/mabulnaga/placenta-flattening) (confidence: medium) * **[Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning](https://arxiv.org/abs/2110.00394v1)** - [Code](https://github.com/cityu-aim-group/prr-fl) (confidence: medium) * **[EMA: Auditing Data Removal from Trained Models](https://arxiv.org/abs/2109.03675v2)** - [Code](https://github.com/hazelsuko07/ema) (confidence: medium) * **[Efficient Neural Network Approximation of Robust PCA for Automated Analysis of Calcium Imaging Data](https://arxiv.org/abs/2108.01665v1)** - [Code](https://github.com/nicalab/bear) (confidence: medium) * **[Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks](https://arxiv.org/abs/2107.13048v1)** - [Code](https://github.com/mahmoodlab/patch-gcn) (confidence: medium) * **[Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform](https://arxiv.org/abs/2107.05990v1)** - [Code](https://github.com/ai-med/daft) (confidence: medium) * **[Self-Supervised Longitudinal Neighbourhood Embedding](https://arxiv.org/abs/2103.03840v3)** - [Code](https://github.com/ouyangjiahong/longitudinal-neighbourhood-embedding) (confidence: medium) * **[Microtubule Tracking in Electron Microscopy Volumes](https://arxiv.org/abs/2009.08371v1)** - [Code](https://github.com/nilsec/micron) (confidence: medium) * **[Vision-based Estimation of MDS-UPDRS Gait Scores for Assessing Parkinson's Disease Motor Severity](https://arxiv.org/abs/2007.08920v1)** - [Code](https://github.com/mlu355/pd-motor-severity-estimation) (confidence: medium) * **[Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation](https://arxiv.org/abs/2007.08354v2)** - [Code](https://github.com/camma-public/orpose-color) (confidence: medium) * **[Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs By Comparing Image Representations](https://arxiv.org/abs/2007.07423v3)** - [Code](https://github.com/funnyzhou/c2l_miccai2020) (confidence: medium) * **[Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement](https://arxiv.org/abs/2007.14472v1)** - [Code](https://github.com/clatfd/gnn-artlabel) (confidence: medium) * **[A Baseline Approach for AutoImplant: the MICCAI 2020 Cranial Implant Design Challenge](https://arxiv.org/abs/2006.12449v2)** - [Code](https://github.com/jianningli/autoimplant) (confidence: medium) * **[Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses](https://arxiv.org/abs/1909.05926v5)** - [Code](https://github.com/lalonderodney/x-caps) (confidence: medium) * **[Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction](https://arxiv.org/abs/1906.01806v5)** - [Code](https://github.com/liaohaofu/adn) (confidence: medium) * **[BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes](https://arxiv.org/abs/1905.08627v2)** - [Code](https://github.com/mrazvan22/brain-coloring) (confidence: medium) * **[Placental Flattening via Volumetric Parameterization](https://arxiv.org/abs/1903.05044v3)** - [Code](https://github.com/mabulnaga/placenta-flattening) (confidence: medium) * **[LumiPath -- Towards Real-time Physically-based Rendering on Embedded Devices](https://arxiv.org/abs/1903.03837v2)** - [Code](https://github.com/lorafib/lumipath) (confidence: medium) **Repository Topics**: awesome, awesome-list, miccai, miccai2026, medical-imaging, deep-learning, computer-vision, segmentation, reconstruction, classification, medical-image-analysis, artificial-intelligence **Conference Scope**: miccai-all-years **Discovery Mode**: broad **Last Updated**: 2026-06-30 10:58 UTC by GitHub Actions **License**: Apache License 2.0

标签：MICCAI, 医学图像分析, 学术资源, 自动化机器人, 计算机视觉, 论文追踪