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: `801` - Fetched arXiv records: `3103` - Unique arXiv records: `2989` - Filtered (non-target): `0` - Filtered (track): `0` - Filtered (no code links): `2188` | Category | Count | Gap to 1000 | |---|---:|---:| | Segmentation | 360 | 640 | | Reconstruction | 115 | 885 | | Classification | 305 | 695 | | Image Registration | 98 | 902 | | Domain Adaptation | 62 | 938 | | Generative Models | 172 | 828 | | General | 91 | 909 | ## 📊 Segmentation *This list is automatically generated. See any issues? Please open a pull request!* * **[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) * **[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!* * **[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!* * **[VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering](https://arxiv.org/abs/2605.20772v1)** - [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/2605.05161v1)** - [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) * **[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!* * **[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) * **[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!* * **[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!* * **[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) * **[Hierarchical Perfusion Graphs for Tumor Heterogeneity Modeling in Glioma Molecular Subtyping](https://arxiv.org/abs/2605.07156v1)** - [Code](https://github.com/janghana/hiperfgnn) (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) * **[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) * **[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) * **[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!* * **[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) * **[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) * **[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**: 2026-05-25 11:54 UTC by GitHub Actions **License**: Apache License 2.0

标签：Apex, arXiv论文, GitLab, Hugging Face, IaC 扫描, Markdown生成, MICCAI 2026, URL抓取, 代码实现, 代码链接验证, 元数据搜索, 公开代码, 医学AI, 医学图像分割, 图像分类, 图像配准, 图像重建, 学术资源, 数据抓取, 机器人自动化, 机器学习, 每日更新, 深度学习, 生成模型, 研究分类, 自动化更新, 计算机视觉, 论文分类, 论文列表, 论文组织, 逆向工具, 防御加固, 领域适应