{"id":13737297,"url":"https://github.com/JunMa11/MICCAI-OpenSourcePapers","last_synced_at":"2025-05-08T13:33:48.547Z","repository":{"id":48167061,"uuid":"214146401","full_name":"JunMa11/MICCAI-OpenSourcePapers","owner":"JunMa11","description":"MICCAI 2019-2023 Open Source Papers","archived":false,"fork":false,"pushed_at":"2023-11-01T20:25:08.000Z","size":2990,"stargazers_count":1266,"open_issues_count":0,"forks_count":236,"subscribers_count":31,"default_branch":"master","last_synced_at":"2025-03-23T09:23:12.950Z","etag":null,"topics":["deep-learning","medical-imaging"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/JunMa11.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2019-10-10T09:51:14.000Z","updated_at":"2025-03-13T03:45:49.000Z","dependencies_parsed_at":"2023-10-05T17:40:12.019Z","dependency_job_id":"f00aeafa-3d22-4300-9c65-79e56e2c6b3d","html_url":"https://github.com/JunMa11/MICCAI-OpenSourcePapers","commit_stats":{"total_commits":56,"total_committers":4,"mean_commits":14.0,"dds":0.1071428571428571,"last_synced_commit":"2dd1ccb324dadf413dbcbc60b03a5f069baa93c8"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JunMa11%2FMICCAI-OpenSourcePapers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JunMa11%2FMICCAI-OpenSourcePapers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JunMa11%2FMICCAI-OpenSourcePapers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JunMa11%2FMICCAI-OpenSourcePapers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JunMa11","download_url":"https://codeload.github.com/JunMa11/MICCAI-OpenSourcePapers/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253077653,"owners_count":21850361,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","medical-imaging"],"created_at":"2024-08-03T03:01:40.252Z","updated_at":"2025-05-08T13:33:48.516Z","avatar_url":"https://github.com/JunMa11.png","language":null,"funding_links":[],"categories":["Others","**How to contact us**"],"sub_categories":["Update log"],"readme":"# MICCAI 2023 Open-Source Papers\n\n![wordcloud23](https://github.com/JunMa11/MICCAI-OpenSourcePapers/blob/master/WordCloud/WordCloud-MICCAI2023.png)\n\n[MICCAI 2023 PROCEEDINGS](https://conferences.miccai.org/2023/en/PROCEEDINGS.html)\n\n\u003e Please feel free to pull requests for the unlisted open-source papers.\n\n| Title | FirstAuthor | Code |\n|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------|-------------------------------------------------------------------------------------------------------------------------------------|\n| 3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images | Alina F. Dima | [code](https://github.com/alinafdima/3Dseg-mip-depth) |\n| 3D Dental Mesh Segmentation Using Semantics-Based Feature Learning with Graph-Transformer | Fan Duan | [code](https://github.com/df-boy/SGTNet) |\n| 3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D Networks | Heng Cai | [code](https://github.com/HengCai-NJU/3D2DCT) |\n| 3D Mitochondria Instance Segmentation with Spatio-Temporal Transformers | Omkar Thawakar | [code](https://github.com/OmkarThawakar/STT-UNET) |\n| A denoised Mean Teacher for domain adaptive point cloud registration | Alexander Bigalke | [code](https://github.com/uncbiag/robot) |\n| A flexible framework for simulating and evaluating biases in deep learning-based medical image analysis | Emma A.M. Stanley | [code](https://github.com/estanley16/SimBA) |\n| A Model-Agnostic Framework for Universal Anomaly Detection of Multi-Organ and Multi-Modal Images | Yinghao Zhang | [code](https://github.com/lianjizhe/MADDR_code) |\n| A Motion Transformer for Single Particle Tracking in Fluorescence Microscopy Images | Yudong Zhang | [code](https://github.com/imzhangyd/MoTT.git) |\n| A Multi-Task Method for Immunofixation Electrophoresis Image Classification | Yi Shi | [code](https://github.com/shiy19/IFE-classification) |\n| A Multi-Task Network for Anatomy Identification in Endoscopic Pituitary Surgery | Adrito Das | [code](https://github.com/dreets/pitnet-anat-public) |\n| A Patient-Specific Self-supervised Model for Automatic X-ray/CT Registration | Baochang Zhang | [code](https://github.com/BaochangZhang/PSSS_registration) |\n| A Privacy-Preserving Walk in the Latent Space of Generative Models for Medical Applications | Matteo Pennisi | [code](https://github.com/perceivelab/PLAN) |\n| A Reliable and Interpretable Framework of Multi-view Learning for Liver Fibrosis Staging | Zheyao Gao | [code](https://github.com/key1589745/Multi-view_liver) |\n| A Sheaf Theoretic Perspective for Robust Prostate Segmentation | Ainkaran Santhirasekaram | [code](https://github.com/AinkaranSanthi/A-Sheaf-Theoretic-Perspective-for-Robust-Segmentation) |\n| A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos | Chao Qin | [code](https://github.com/AlfredQin/STNet) |\n| A Transfer Learning Approach to Localise a Deep Brain Stimulation Target | Ying-Qiu Zheng | [code](https://git.fmrib.ox.ac.uk/yqzheng1/python-localise) |\n| A Video-based End-to-end Pipeline for Non-nutritive Sucking Action Recognition and Segmentation in Young Infants | Shaotong Zhu | [code](https://github.com/ostadabbas/NNS-Detection-and-Segmentation) |\n| A2FSeg: Adaptive Multi-Modal Fusion Network for Medical Image Segmentation | Zirui Wang | [code](https://github.com/Zirui0623/A2FSeg.git) |\n| ACC-UNet: A Completely Convolutional UNet model for the 2020s | Nabil Ibtehaz | [code](https://github.com/kiharalab/ACC-UNet) |\n| Accurate multi-contrast MRI super-resolution via a dual cross-attention transformer network | Shoujin Huang | [code](https://github.com/mylyu/M4Raw) |\n| ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast | Chenyu You | [code](https://github.com/charlesyou999648/ACTION) |\n| Adapter Learning in Pretrained Feature Extractor for Continual Learning of Diseases | Wentao Zhang | [code](https://github.com/GiantJun/CL_Pytorch) |\n| Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation | Muhammad Asad | [code](https://github.com/masadcv/MONet-MONAILabel) |\n| Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation | Jingna Qiu | [code](https://github.com/DeepMicroscopy/AdaptiveRegionSelection) |\n| Adaptive Supervised PatchNCE Loss for Learning H\u0026E-to-IHC Stain Translation with Inconsistent Groundtruth Image Pairs | Fangda Li | [code](https://github.com/lifangda01/AdaptiveSupervisedPatchNCE) |\n| Adjustable Robust Transformer for High Myopia Screening in Optical Coherence Tomography | Xiao Ma | [code](https://github.com/maxiao0234/ARTran) |\n| Adult-like Phase and Multi-scale Assistance for Isointense Infant Brain Tissue Segmentation | Jiameng Liu | [code](https://github.com/SaberPRC/IsointenseBrainTissueSeg.git) |\n| AirwayFormer: Structure-Aware Boundary-Adaptive Transformers for Airway Anatomical Labeling | Weihao Yu | [code](https://github.com/yuyouxixi/airway-labeling/tree/main) |\n| Alias-Free Co-Modulated Network for Cross-Modality Synthesis and Super-Resolution of MR Images | Zhiyun Song | [code](https://github.com/zhiyuns/AFCM) |\n| ALL-IN: A Local GLobal Graph-based DIstillatioN Model for Representation Learning of Gigapixel Histopathology Images With Application In Cancer Risk Assessment | Puria Azadi | [code](https://github.com/pazadimo/ALL-IN) |\n| AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain Tumor | Yu-Jen Chen | [code](https://github.com/windstormer/AME-CAM) |\n| An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment | Parmida Ghahremani | [code](https://github.com/nadeemlab/DeepLIIF) |\n| An Anti-Biased TBSRTC-Category Aware Nuclei Segmentation Framework with A Multi-Label Thyroid Cytology Benchmark | Junchao Zhu | [code](https://github.com/Junchao-Zhu/TCSegNet) |\n| An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field | Kelly Payette | [code](https://github.com/SVRTK/Fetal-T2star-Recon) |\n| An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis | Luyi Han | [code](https://github.com/fiy2W/mri_seq2seq) |\n| An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment | Favour Nerrise | [code](https://github.com/favour-nerrise/xGW-GAT) |\n| An Unsupervised Multispectral Image Registration Network for Skin Diseases | Songhui Diao | [code](https://github.com/SH-Diao123/MSIR) |\n| Anatomical Landmark Detection Using a Multiresolution Learning Approach with a Hybrid Transformer-CNN Model | Thanaporn Viriyasaranon | [code](https://github.com/seriee/Multiresolution-HTC.git) |\n| Anatomy-Driven Pathology Detection on Chest X-rays | Philip M¨¹ller | [code](https://github.com/philip-mueller/adpd) |\n| Anatomy-informed Data Augmentation for Enhanced Prostate Cancer Detection | Balint Kovacs | [code](https://github.com/MIC-DKFZ/batchgenerators) |\n| Aneurysm Pose Estimation with Deep Learning | Youssef Assis | [code](https://gitlab.inria.fr/yassis/DeepAnePose) |\n| AngioMoCo: Learning-based Motion Correction in Cerebral Digital Subtraction Angiography | Ruisheng Su | [code](https://github.com/RuishengSu/AngioMoCo) |\n| Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models | Tomer Amit | [code](https://github.com/tomeramit/Annotator-Consensus-Prediction) |\n| Ariadne¡®s Thread: Using Text Prompts to Improve Segmentation of Infected Areas from Chest X-ray images | Yi Zhong | [code](https://github.com/HUANGLIZI/LViT) |\n| ArSDM: Colonoscopy Images Synthesis with Adaptive Refinement Semantic Diffusion Models | Yuhao Du | [code](https://github.com/DuYooho/ArSDM) |\n| Artifact Restoration in Histology Images with Diffusion Probabilistic Models | Zhenqi He | [code](https://github.com/lu-yizhou/ClusterSeg) |\n| ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising | Zhihao Chen | [code](https://github.com/hao1635/ASCON) |\n| Asymmetric Contour Uncertainty Estimation for Medical Image Segmentation | Thierry Judge | [code](https://github.com/ThierryJudge/contouring-uncertainty) |\n| Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer’s Disease using Multimodal Imaging Genetics | Rong Zhou | [code](https://github.com/rongzhou7/ADCCA) |\n| atTRACTive: Semi-automatic white matter tract segmentation using active learning | Robin Peretzke | [code](https://github.com/MIC-DKFZ/MITK-Diffusion) |\n| Automatic Bleeding Risk Rating System of Gastric Varices | Yicheng Jiang | [code](https://github.com/LuyueShi/gastric-varices) |\n| Automatic Retrieval of Corresponding US Views in Longitudinal Examinations | Hamideh Kerdegari | [code](https://github.com/hamidehkerdegari/Muscle-view-retrieval) |\n| Automatic Segmentation of Internal Tooth Structure from CBCT Images using Hierarchical Deep Learning | SaeHyun Kim | [code](https://github.com/Saeeeae/Internal-Tooth-Segmentation) |\n| BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation | Tao Chen | [code](https://github.com/takimailto/BerDiff) |\n| Beyond the Snapshot: Brain Tokenized Graph Transformer for Longitudinal Brain Functional Connectome Embedding | Zijian Dong | [code](https://github.com/ZijianD/Brain-TokenGT.git) |\n| Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data | Kai Ye | [code](https://github.com/FlynnYe/BMCL) |\n| Boosting Breast Ultrasound Video Classification by the Guidance of Keyframe Feature Centers | Anlan Sun | [code](https://github.com/PlayerSAL/KGA-Net) |\n| Boundary Difference Over Union Loss For Medical Image Segmentation | Fan Sun | [code](https://github.com/sunfan-bvb/BoundaryDoULoss) |\n| Boundary-weighted logit consistency improves calibration of segmentation networks | Neerav Karani | [code](https://github.com/neerakara/BWCR) |\n| Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI | Lintao Zhang | [code](https://github.com/goodaycoder/BAR) |\n| BrainUSL: Unsupervised Graph Structure Learning for Functional Brain Network Analysis | Pengshuai Zhang | [code](https://github.com/IntelliDAL/Graph/tree/main/BrainUSL) |\n| Bridging ex-vivo training and intra-operative deployment for surgical margin assessment with Evidential Graph Transformer | Amoon Jamzad | [code](https://github.com/med-i-lab/evidential_graph_transformers/) |\n| Can point cloud networks learn statistical shape models of anatomies? | Jadie Adams | [code](https://github.com/jadie1/PointCompletionSSM) |\n| CARL: Cross-aligned Representation Learning for Multi-view Lung Cancer Histology Classification | Yin Luo | [code](https://github.com/candyknife/CARL) |\n| CAS-Net: Cross-view Aligned Segmentation by Graph Representation of Knees | Zixu Zhuang | [code](https://github.com/zixuzhuang/OAI_seg) |\n| CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery | Long Bai | [code](https://github.com/longbai1006/CAT-ViL) |\n| CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI? | Jiahao Huang | [code](https://github.com/ayanglab/CDiffMR) |\n| CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification | Zhenrong Shen | [code](https://github.com/ZhenrongShen/CellGAN) |\n| Centroid-aware feature recalibration for cancer grading in pathology images | Jaeung Lee | [code](https://github.com/QuIIL/KBSMC_colon_cancer_grading_dataset) |\n| Certification of Deep Learning Models for Medical Image Segmentation | Othmane Laousy | [code](https://github.com/othmanela/medical_cert_seg) |\n| Chest X-ray Image Classification: A Causal Perspective | Weizhi Nie | [code](https://github.com/zc2024/Causal_CXR) |\n| CheXstray: A Real-Time Multi-Modal Monitoring Workflow for Medical Imaging AI | Jameson Merkow | [code](https://github.com/microsoft/MedImaging-ModelDriftMonitoring) |\n| CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention | Hengxu Zhang | [code](https://github.com/zhanghx-iim-ahu/CircleFormer) |\n| CL-ADDA: Contrastive Learning with Amplitude-Driven Data Augmentation for fMRI-Based Individualized Predictions | Jiangcong Liu | [code](https://github.com/tianbjtu/CL-ADDA.git) |\n| Class-Aware Feature Alignment for Domain Adaptative Mitochondria Segmentation | Dan Yin | [code](https://github.com/Danyin813/CAFA.) |\n| Client-Level Differential Privacy via Adaptive Intermediary in Federated Medical Imaging | Meirui Jiang | [code](https://github.com/med-air/Client-DP-FL) |\n| CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation | Yicheng Wu | [code](https://github.com/ycwu1997/CoactSeg) |\n| Co-assistant Networks for Label Correction | Xuan Chen | [code](https://github.com/shannak-chen/CNLC) |\n| CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis | Lan Jiang | [code](https://github.com/SeeMeInCrown/CoLa_Diff_MultiModal_MRI_Synthesis) |\n| Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration | Yang Liu | [code](https://github.com/brain-intelligence-lab/GIRNet) |\n| Collaborative modality generation and tissue segmentation for early-developing macaque brain MR images | Xueyang Wu | [code](https://github.com/XueyangWWW/CSGF) |\n| COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation | Han Liu | [code](https://github.com/han-liu/COLosSAL) |\n| Combat Long-tails in Medical Classification with Relation-aware Consistency and Virtual Features Compensation | Li Pan | [code](https://github.com/jhonP-Li/MRC_VFC) |\n| Combating Medical Label Noise via Robust Semi-supervised Contrastive Learning | Bingzhi Chen | [code](https://github.com/Binz-Chen/MICCAI2023_SSCL) |\n| Community-Aware Transformer for Autism Prediction in fMRI Connectome | Anushree Bannadabhavi | [code](https://github.com/ubc-tea/Com-BrainTF) |\n| Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation | Xinrong Hu | [code](https://github.com/xhu248/cond_ddpm_wsss) |\n| Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction | Qiang Ma | [code](https://github.com/m-qiang/CoTAN) |\n| Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation | Qingyue Wei | [code](https://github.com/yulequan/UA-MT/tree/88ed29ad794f877122e542a7fa9505a76fa83515/data) |\n| Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation | Zheang Huai | [code](https://github.com/xmed-lab/CPR) |\n| Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction | Zeyu Han | [code](https://github.com/Show-han/PET-Reconstruction) |\n| Contrastive Feature Decoupling for Weakly-supervised Disease Detection | Jhih-Ciang Wu | [code](https://github.com/Jhih-Ciang/PANDA-MIL) |\n| Contrastive Masked Image-Text Modeling for Medical Visual Representation Learning | Cheng Chen | [code](https://github.com/cchen-cc/CMITM) |\n| ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation | Xian Lin | [code](https://github.com/xianlin7/ConvFormer) |\n| cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations | Silvia D. Almeida | [code](https://github.com/MIC-DKFZ/cOOpD) |\n| Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation | Shengbo Gao | [code](https://github.com/Herschel555/CAML) |\n| CorSegRec: A Topology-Preserving Scheme for Extracting Fully-Connected Coronary Arteries from CT Angiography | Yuehui Qiu | [code](https://github.com/YH-Qiu/CorSegRec) |\n| CortexMorph: fast cortical thickness estimation via diffeomorphic registration using VoxelMorph | Richard McKinley | [code](https://github.com/SCAN-NRAD/CortexMorph) |\n| COVID-19 Pneumonia Classification with Transformer from Incomplete Modalities | Eduard Lloret Carbonell | [code](https://github.com/edurbi/MICCAI2023) |\n| Cross-adversarial local distribution regularization for semi-supervised medical image segmentation | Thanh Nguyen-Duc | [code](https://github.com/PotatoThanh/Cross-adversarial-local-distribution-regularization) |\n| Cross-Dataset Adaptation for Instrument Classification in Cataract Surgery Videos | Jay N. Paranjape | [code](https://github.com/JayParanjape/Barlow-Adaptor) |\n| Cross-modulated Few-shot Image Generation for Colorectal Tissue Classification | Amandeep Kumar | [code](https://github.com/VIROBO-15/XM-GAN) |\n| CT Kernel Conversion Using Multi-Domain Image-to-Image Translation with Generator-Guided Contrastive Learning | Changyong Choi | [code](https://github.com/cychoi97/GGCL) |\n| CTFlow: Mitigating Effects of Computed Tomography Acquisition and Reconstruction with Normalizing Flows | Leihao Wei | [code](https://github.com/hsu-lab/ctflow) |\n| CXR-CLIP: Toward Large Scale Chest X-ray Language-Image Pre-training | Kihyun You | [code](https://github.com/kakaobrain/cxr-clip) |\n| CycleSTTN: A Learning-Based Temporal Model for Specular Augmentation in Endoscopy | Rema Daher | [code](https://github.com/RemaDaher/CycleSTTN) |\n| DARC: Distribution-Aware Re-Coloring Model for Generalizable Nucleus Segmentation | Shengcong Chen | [code](https://github.com/csccsccsccsc/DARC) |\n| DAS-MIL: Distilling Across Scales for MIL Classification of Histological WSIs | Gianpaolo Bontempo | [code](https://github.com/aimagelab/mil4wsi) |\n| Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models | Mitchell Pavlak | [code](https://github.com/mpavlak25/data-audit) |\n| DBTrans: A Dual-Branch Vision Transformer for Multi-modal Brain Tumor Segmentation | Xinyi Zeng | [code](https://github.com/Aru321/DBTrans) |\n| Decoupled Consistency for Semi-supervised Medical Image Segmentation | Faquan Chen | [code](https://github.com/wxfaaaaa/DCNet) |\n| DeDA: Deep Directed Accumulator | Hang Zhang | [code](https://github.com/tinymilky/DeDA) |\n| Deep Homography Prediction for Endoscopic Camera Motion Imitation Learning | Martin Huber | [code](https://github.com/RViMLab/homography_imitation_learning) |\n| Deep Learning for Tumor-associated Stroma Identification in Prostate Histopathology Slides | Zichen Wang | [code](https://github.com/zcwang0702/DeepFieldEffect_StromaNet) |\n| Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacy | Kai Packh?user | [code](https://github.com/kaipackhaeuser/PriCheXy-Net) |\n| Deep Mutual Distillation for Semi-Supervised Medical Image Segmentation | Yushan Xie | [code](https://github.com/SilenceMonk/Dual-Mutual-Distillation) |\n| Deep unsupervised clustering for conditional identification of subgroups within a digital pathology image set | Mariia Sidulova | [code](https://github.com/DIDSR/DomId) |\n| DeepGraphDMD: Interpretable Spatio-Temporal Decomposition of Non-linear Functional Brain Network Dynamics | Md Asadullah Turja | [code](https://github.com/mturja-vf-ic-bd/DeepGraphDMD) |\n| DeepSOZ: A Robust Deep Model for Joint Temporal and Spatial Seizure Onset Localization from Multichannel EEG Data | Deeksha M. Shama | [code](https://github.com/deeksha-ms/DeepSOZ.git) |\n| Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning | Ruining Deng | [code](https://github.com/hrlblab/MolecularEL) |\n| Deployment of Image Analysis Algorithms under Prevalence Shifts | Patrick Godau | [code](https://github.com/IMSY-DKFZ/prevalence-shifts) |\n| Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery | Baoru Huang | [code](https://github.com/br0202/Sensing_area_detection.git) |\n| Detection-free Pipeline for Cervical Cancer Screening of Whole Slide Images | Maosong Cao | [code](https://github.com/thebestannie/Detection-free-MICCAI2023) |\n| Developing Large Pre-trained Model for Breast Tumor Segmentation from Ultrasound Images | Meiyu Li | [code](https://github.com/limy-ulab/US-SEG) |\n| Development and Fast Transferring of General Connectivity-based Diagnosis Model to New Brain Disorders with Adaptive Graph Meta-learner | Yuxiao Liu | [code](https://github.com/dasklarleo/fMRI_meta/tree/main) |\n| Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation | Shishuai Hu | [code](https://github.com/ShishuaiHu/CCSDG) |\n| DHC: Dual-debiased Heterogeneous Co-training Framework for Class-imbalanced Semi-supervised Medical Image Segmentation | Haonan Wang | [code](https://github.com/xmed-lab/DHC) |\n| Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels | Zifu Wang | [code](https://github.com/zifuwanggg/JDTLosses) |\n| DiffDP: Radiotherapy Dose Prediction via a Diffusion Model | Zhenghao Feng | [code](https://github.com/scufzh/DiffDP) |\n| Differentiable Beamforming for Ultrasound Autofocusing | Walter Simson | [code](https://github.com/waltsims/dbua) |\n| DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification | Yijun Yang | [code](https://github.com/scott-yjyang/DiffMIC) |\n| DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets | Hyun-Jic Oh | [code](https://github.com/hvcl/DiffMix) |\n| DiffULD: Diffusive Universal Lesion Detection | Peiang Zhao | [code](https://github.com/momopusheen/DiffULD) |\n| Diffusion Kinetic Model for Breast Cancer Segmentation in Incomplete DCE-MRI | Tianxu Lv | [code](https://github.com/Medical-AI-Lab-of-JNU/DKM) |\n| Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays | Ibrahim Ethem Hamamci | [code](https://github.com/ibrahimethemhamamci/DENTEX) |\n| DISA: DIfferentiable Similarity Approximation for Universal Multimodal Registration | Matteo Ronchetti | [code](https://github.com/ImFusionGmbH/DISA-universal-multimodal-registration) |\n| DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms using Self-adversarial Learning | Xin Wang | [code](https://github.com/xinwangxinwang/DisAsymNet) |\n| DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution | Ye Mao | [code](https://github.com/Yebulabula/DisC-Diff) |\n| Distilling BlackBox to Interpretable models for Efficient Transfer Learning | Shantanu Ghosh | [code](https://github.com/batmanlab/MICCAI-2023-Route-interpret-repeat-CXRs#downloading-data) |\n| Distributionally Robust Image Classifiers for Stroke Diagnosis in Accelerated MRI | Boran Hao | [code](https://github.com/noc-lab/drl_mri) |\n| DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction | Xiaoxiao He | [code](https://github.com/hexiaoxiao-cs/DMCVR) |\n| Do we really need that skip-connection? Understanding its interplay with task complexity | Amith Kamath | [code](https://github.com/amithjkamath/to_skip_or_not) |\n| Domain Adaptation for Medical Image Segmentation using Transformation-Invariant Self-Training | Negin Ghamsarian | [code](https://github.com/Negin-Ghamsarian/Transformation-Invariant-Self-Training-MICCAI23) |\n| Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI | Henry F. J. Tregidgo | [code](https://github.com/htregidgo/joint_diffusion_structural_seg) |\n| Dose Guidance for Radiotherapy-oriented Deep Learning Segmentation | Elias R¨¹fenacht | [code](https://github.com/ruefene/doselo) |\n| DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image Synthesis | Zhiwen Yang | [code](https://github.com/Yaziwel/Multi-Center-PET-Image-Synthesis) |\n| Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRI | Jiamiao Zhang | [code](https://github.com/jmzhang79/Dual-ArbNet) |\n| Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos | Divyanshu Mishra | [code](https://github.com/FetalUltrasound/DCDM) |\n| Dual Domain Motion Artifacts Correction for MR Imaging Under Guidance of K-space Uncertainty | Jiazhen Wang | [code](https://github.com/Jiazhen-Wang/D2MC-Net-main) |\n| Dynamic Curriculum Learning via In-Domain Uncertainty for Medical Image Classification | Chaoyi Li | [code](https://github.com/Joey2117/DCLU) |\n| Dynamic Graph Neural Representation Based Multi-modal Fusion Model for Cognitive Outcome Prediction in Stroke Cases | Shuting Liu | [code](https://github.com/fightingkitty/MHGSA) |\n| Dynamic Structural Brain Network Construction by Hierarchical Prototype Embedding GCN using T1-MRI | Yilin Leng | [code](https://github.com/Leng-10/DH-ProGCN) |\n| EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms | Masoud Mokhtari | [code](https://github.com/MasoudMo/echoglad) |\n| ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification | Yilan Zhang | [code](https://github.com/zylbuaa/ECL.git) |\n| EdgeAL: An Edge Estimation Based Active Learning Approach for OCT Segmentation | Md Abdul Kadir | [code](https://github.com/Mak-Ta-Reque/EdgeAL) |\n| EdgeMixup: Embarrassingly Simple Data Alteration to Improve Lyme Disease Lesion Segmentation and Diagnosis Fairness | Haolin Yuan | [code](https://github.com/Haolin-Yuan/EdgeMixup) |\n| Efficient Subclass Segmentation in Medical Images | Linrui Dai | [code](https://github.com/OvO1111/EfficientSubclassLearning) |\n| EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation | Jiacheng Ruan | [code](https://github.com/JCruan519/EGE-UNet) |\n| Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation | Maximilian Rohleder | [code](https://github.com/maxrohleder/FUME) |\n| Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning | Aditya Murali | [code](https://github.com/CAMMA-public/SurgLatentGraph) |\n| EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos | Ruyi Zha | [code](https://github.com/Ruyi-Zha/endosurf.git) |\n| EoFormer: Edge-oriented Transformer for Brain Tumor Segmentation | Dong She | [code](https://github.com/sd0809/EoFormer) |\n| EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition | Siyuan Yan | [code](https://github.com/jeremykawahara/derm7pt) |\n| Estimated time to surgical procedure completion: An exploration of video analysis methods | Barak Ariel | [code](https://github.com/theator/etc) |\n| Evidence Reconciled Neural Network for Out-of-Distribution Detection in Medical Images | Wei Fu | [code](https://github.com/KellaDoe/ERNN) |\n| Evolutionary normalization optimization boosts semantic segmentation network performance | Luisa Neubig | [code](https://github.com/neuluna/ga-unet) |\n| Explainable Image Classification with Improved Trustworthiness for Tissue Characterisation | Alfie Roddan | [code](https://github.com/alfieroddan/Explainable-Image-Classification) |\n| Exploring Brain Function-Structure Connectome Skeleton via Self-Supervised Graph-Transformer Approach | Yanqing Kang | [code](https://github.com/kang105/TSGR) |\n| Exploring Unsupervised Cell Recognition with Prior Self-activation Maps | Pingyi Chen | [code](https://github.com/cpystan/PSM) |\n| Eye-Guided Dual-Path Network for Multi-organ Segmentation of Abdomen | Chong Wang | [code](https://github.com/code-Porunacabeza/gaze_seg/) |\n| Factor Space and Spectrum for Medical Hyperspectral Image Segmentation | Boxiang Yun | [code](https://github.com/boxiangyun/Dual-Stream-MHSI) |\n| FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification | Zikang Xu | [code](https://github.com/XuZikang/FairAdaBN) |\n| Faithful Synthesis of Low-dose Contrast-enhanced Brain MRI Scans using Noise-preserving Conditional GANs | Thomas Pinetz | [code](https://github.com/tpinetz/low-dose-gadolinium-mri-synthesis) |\n| Fast Reconstruction for Deep Learning PET Head Motion Correction | Tianyi Zeng | [code](https://github.com/OnofreyLab/dl-hmc_fast_recon_miccai2023) |\n| Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis | Hadrien Reynaud | [code](https://github.com/HReynaud/EchoDiffusion) |\n| FEDD - Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification | He?ctor Carrio?n | [code](https://github.com/hectorcarrion/fedd) |\n| FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification | Nannan Wu | [code](https://github.com/wnn2000/FedIIC) |\n| FedSoup: Improving Generalization and Personalization in Federated Learning via Selective Model Interpolation | Minghui Chen | [code](https://github.com/ubc-tea/FedSoup) |\n| FE-STGNN: Spatio-Temporal Graph Neural Network with Functional and Effective Connectivity Fusion for MCI Diagnosis | Dongdong Chen | [code](https://github.com/haijunkenan/FE-STGNN) |\n| FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling | Faris Almalik | [code](https://github.com/faresmalik/FeSViBS) |\n| Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer | Yazhou Zhu | [code](https://github.com/YazhouZhu19/RPT) |\n| Fine-grained Hand Bone Segmentation via Adaptive Multi-dimensional Convolutional Network and Anatomy-constraint Loss | Bolun Zeng | [code](https://github.com/BL-Zeng/AMCNet) |\n| Forensic Histopathological Recognition via a Context-Aware MIL Network Powered by Self-Supervised Contrastive Learning | Chen Shen | [code](https://github.com/ladderlab-xjtu/forensic_pathology) |\n| Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train | Zhao Wang | [code](https://github.com/openmedlab/Endo-FM) |\n| FreeSeed: Frequency-band-aware and Self-guided Network for Sparse-view CT Reconstruction | Chenglong Ma | [code](https://github.com/Masaaki-75/freeseed) |\n| Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation | Asif Hanif | [code](https://github.com/asif-hanif/vafa) |\n| Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation | Heng Li | [code](https://github.com/liamheng/Non-IID_Medical_Image_Segmentation) |\n| From Mesh Completion to AI Designed Crown | Golriz Hosseinimanesh | [code](https://github.com/Golriz-code/DMC.git) |\n| FSDiffReg: Feature-wise and Score-wise Diffusion-guided Unsupervised Deformable Image Registration for Cardiac Images | Yi Qin | [code](https://github.com/xmed-lab/FSDiffReg.git) |\n| Fully Bayesian VIB-DeepSSM | Jadie Adams | [code](https://github.com/jadie1/BVIB-DeepSSM) |\n| Fundus-Enhanced Disease-Aware Distillation Model for Retinal Disease Classification from OCT Images | Lehan Wang | [code](https://github.com/li-xirong/mmc-amd) |\n| Gadolinium-Free Cardiac MRI Myocardial Scar Detection by 4D Convolution Factorization | Amine Amyar | [code](https://github.com/HMS-CardiacMR/Myocardial_Scar_Detection) |\n| Gall Bladder Cancer Detection from US Images with Only Image Level Labels | Soumen Basu | [code](https://gbc-iitd.github.io/gbcu) |\n| Gene-induced Multimodal Pre-training for Image-omic Classification | Ting Jin | [code](https://github.com/huangwudiduan/GIMP) |\n| Geometry-adaptive Network for Robust Detection of Placenta Accreta Spectrum Disorders | Zailiang Chen | [code](https://github.com/Meteorary/GALA) |\n| GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation | Ziyang Zheng | [code](https://github.com/xmed-lab/GL-Fusion) |\n| GLSFormer : Gated - Long, Short Sequence Transformer for Step Recognition in Surgical Videos | Nisarg A. Shah | [code](https://github.com/nisargshah1999/GLSFormer) |\n| GRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging | Ruipeng Zhang | [code](https://github.com/MediaBrain-SJTU/GPFL-GRACE) |\n| GSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration | Haoran Dou | [code](https://github.com/wulalago/GSMorph) |\n| Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images | Zdravko Marinov | [code](https://github.com/Zrrr1997/Guiding-The-Guidance) |\n| H2GM: A Hierarchical Hypergraph Matching Framework for Brain Landmark Alignment | Zhibin He | [code](https://github.com/CUHK-AIM-Group/HHGM) |\n| HACL-Net: Hierarchical Attention and Contrastive Learning Network for MRI-Based Placenta Accreta Spectrum Diagnosis | Mingxuan Lu | [code](https://github.com/LouieBHLu/HACL-Net) |\n| HC-Net: Hybrid Classification Network for Automatic Periodontal Disease Diagnosis | Lanzhuju Mei | [code](https://github.com/ShanghaiTech-IMPACT/Periodental_Disease) |\n| H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation | Jun Shi | [code](https://github.com/shijun18/H-DenseFormer) |\n| HENet: Hierarchical Enhancement Network for Pulmonary Vessel Segmentation in Non-contrast CT Images | Wenqi Zhou | [code](https://github.com/CODESofWenqi/HENet) |\n| Hierarchical Vision Transformers for Disease Progression Detection in Chest X-Ray Images | Amarachi B. Mbakwe | [code](https://github.com/PLAN-Lab/CheXRelFormer) |\n| High-Quality Virtual Single-Viewpoint Surgical Video: Geometric Autocalibration of Multiple Cameras in Surgical Lights | Yuna Kato | [code](https://github.com/isogawalab/SingleViewSurgicalVideo) |\n| High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers | Marek Wodzinski | [code](https://github.com/MWod/DeepImplant_MICCAI_2023) |\n| HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis | Ziyu Guo | [code](https://github.com/HKU-MedAI/HIGT) |\n| Histopathology Image Classification using Deep Manifold Contrastive Learning | Jing Wei Tan | [code](https://github.com/hvcl/Deep-Manifold-Contrastive-Learning) |\n| How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers? | Gregory Holste | [code](https://github.com/VITA-Group/PruneCXR) |\n| How Reliable are the Metrics Used for Assessing Reliability in Medical Imaging? | Mayank Gupta | [code](https://github.com/MayankGupta73/Robust-Calibration) |\n| IIB-MIL: Integrated instance-level and bag-level multiple instances learning with label disambiguation for pathological image analysis | Qin Ren | [code](https://github.com/TencentAILabHealthcare/IIB-MIL) |\n| Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts | Chenyu You | [code](https://github.com/charlesyou999648/MORSE) |\n| Implicit neural representations for joint decomposition and registration of gene expression images in the marmoset brain | Michal Byra | [code](https://gene-atlas.brainminds.jp/) |\n| Improved Multi-Shot Diffusion-Weighted MRI with Zero-Shot Self-Supervised Learning Reconstruction | Jaejin Cho | [code](https://github.com/jaejin-cho/miccai2023) |\n| Improving Automatic Fetal Biometry Measurement with Swoosh Activation Function | Shijia Zhou | [code](https://github.com/DasuberVetLeonidas/SwooshActivationFunction) |\n| Incomplete Multimodal Learning for Visual Acuity Prediction after Cataract Surgery Using Masked Self-Attention | Qian Zhou | [code](https://github.com/liyiersan/MSA) |\n| Instructive Feature Enhancement for Dichotomous Medical Image Segmentation | Lian Liu | [code](https://github.com/yezi-66/IFE) |\n| Interpretable Medical Image Classification using Prototype Learning and Privileged Information | Luisa Gall¨¦e | [code](https://github.com/XRad-Ulm/Proto-Caps) |\n| Intraoperative CT augmentation for needle-based liver interventions | Sidaty El hadramy | [code](https://github.com/Sidaty1/Intraoperative_CT_augmentation) |\n| Inverse Consistency by Construction for Multistep Deep Registration | Hastings Greer | [code](https://github.com/uncbiag/ByConstructionICON) |\n| InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model | Jueqi Wang | [code](https://github.com/BioMedAI-UCSC/InverseSR) |\n| Ischemic stroke segmentation from a cross-domain representation in multimodal diffusion studies | Santiago G¨®mez | [code](https://gitlab.com/bivl2ab/research/2023-cross-domain-stroke-segmentation) |\n| Iteratively Coupled Multiple Instance Learning from Instance to Bag Classifier for Whole Slide Image Classification | Hongyi Wang | [code](https://github.com/Dootmaan/ICMIL) |\n| Joint Dense-Point Representation for Contour-Aware Graph Segmentation | Kit Mills Bransby | [code](https://github.com/kitbransby/Joint_Graph_Segmentation) |\n| Joint optimization of a ¦Â-VAE for ECG task-specific feature extraction | Viktor van der Valk | [code](https://github.com/ViktorvdValk/Task-Specific-VAE) |\n| Joint Segmentation and Sub-Pixel Localization in Structured Light Laryngoscopy | Jann-Ole Henningson | [code](https://github.com/Henningson/HLEDataset) |\n| Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training | Xiaofei Chen | [code](https://github.com/ChenXiaoFei-CS/KoBo) |\n| Label-preserving Data Augmentation in Latent Space for Diabetic Retinopathy Recognition | Zhihao Zhao | [code](https://github.com/AIEyeSystem/LpDA) |\n| LABRAD-OR: Lightweight Memory Scene Graphs for Accurate Bimodal Reasoning in Dynamic Operating Rooms | Ege ?zsoy | [code](https://github.com/egeozsoy/4D-OR) |\n| Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection | Reza Azad | [code](https://github.com/mindflow-institue/Laplacian-Former) |\n| Learnable Query Initialization for Surgical Instrument Instance Segmentation | Rohan Raju Dhanakshirur | [code](https://github.com/AINeurosurgery/Learnable-QPD-for-maskDINO) |\n| Learnable Subdivision Graph Neural Network for Functional Brain Network Analysis and Interpretable Cognitive Disorder Diagnosis | Dongdong Chen | [code](https://github.com/haijunkenan/LSGNN) |\n| Learned Alternating Minimization Algorithm for Dual-Domain Sparse-View CT Reconstruction | Chi Ding | [code](https://github.com/chrisdcs/LAMA-Learned-Alternating-Minimization-Algorithm) |\n| Learning Asynchronous Common and Individual Functional Brain Network for AD Diagnosis | Xiang Tang | [code](https://github.com/seuzjj/ACIFBN) |\n| Learning Deep Intensity Field for Extremely Sparse-View CBCT Reconstruction | Yiqun Lin | [code](https://github.com/xmed-lab/DIF-Net) |\n| Learning Expected Appearances for Intraoperative Registration during Neurosurgery | Nazim Haouchine | [code](https://github.com/rouge1616/ExApp/) |\n| Learning normal asymmetry representations for homologous brain structures | Duilio Deangeli | [code](https://github.com/duiliod/DeepNORHA) |\n| Learning Ontology-based Hierarchical Structural Relationship for Whole Brain Segmentation | Junyan Lyu | [code](https://github.com/CRazorback/OHSR) |\n| Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation | Nilesh Kumar | [code](https://github.com/nileshkumar0726/Learning_Transformations) |\n| Learning with Domain-Knowledge for Generalizable Prediction of Alzheimer’s Disease from Multi-Site Structural MRI | Yanjie Zhou | [code](https://github.com/Yanjie-Z/DomainKnowledge4AD) |\n| Learning with Synthesized Data for Generalizable Lesion Detection in Real PET Images | Xinyi Yang | [code](https://github.com/xyang258/livdetSDG) |\n| Lesion-aware Contrastive Learning for Diabetic Retinopathy Diagnosis | Shuai Cheng | [code](https://github.com/IntelliDAL/Image) |\n| LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion | Long Bai | [code](https://github.com/longbai1006/LLCaps) |\n| Localized Questions in Medical Visual Question Answering | Sergio Tascon-Morales | [code](https://github.com/sergiotasconmorales/locvqa) |\n| Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures From Routine EHRs for Pulmonary Nodule Classification | Thomas Z. Li | [code](https://github.com/MASILab/lmsignatures) |\n| LOTUS: Learning to Optimize Task-based US representations | Yordanka Velikova | [code](https://github.com/danivelikova/lotus) |\n| Low-dose CT image super-resolution network with dual-guidance feature distillation and dual-path content communication | Jianning Chi | [code](https://github.com/neu-szy/dual-guidance_LDCT_SR) |\n| LSOR: Longitudinally-Consistent Self-Organized Representation Learning | Jiahong Ouyang | [code](https://github.com/ouyangjiahong/longitudinal-som-single-modality) |\n| LUCYD: A Feature-Driven Richardson-Lucy Deconvolution Network | Tom¨¢? Chobola | [code](https://github.com/ctom2/lucyd-deconvolution/) |\n| Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging | Ke Xiao | [code](https://github.com/Information-Fusion-Lab-Umass/CUSSP_UKB_MR) |\n| Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks | Matthew Baugh | [code](https://github.com/matt-baugh/pytorch-poisson-image-editing) |\n| Masked Frequency Consistency for Domain-Adaptive Semantic Segmentation of Laparoscopic Images | Xinkai Zhao | [code](https://github.com/MoriLabNU/MFC) |\n| Masked Vision and Language Pre-training with Unimodal and Multimodal Contrastive Losses for Medical Visual Question Answering | Pengfei Li | [code](https://github.com/pengfeiliHEU/MUMC) |\n| Maximum Entropy on Erroneous Predictions: Improving model calibration for medical image segmentation | Agostina J. Larrazabal | [code](https://github.com/agosl/Maximum-Entropy-on-Erroneous-Predictions/) |\n| Maximum-entropy estimation of joint relaxation-diffusion distribution using multi-TE diffusion MRI | Lipeng Ning | [code](https://github.com/LipengNing/ME-RDD/tree/main/MICCAI_example) |\n| MDA-SR: Multi-level Domain Adaptation Super-Resolution for Wireless Capsule Endoscopy Images | Tianbao Liu | [code](https://github.com/SMU-MedicalVision/MDA-SR) |\n| MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets | Siyi Du | [code](https://github.com/siyi-wind/MDViT) |\n| Medical Boundary Diffusion Model for Skin Lesion Segmentation | Jiacheng Wang | [code](https://github.com/jcwang123/MBDiff) |\n| MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation | Saikat Roy | [code](https://github.com/MIC-DKFZ/MedNeXt) |\n| MEPNet: A Model-Driven Equivariant Proximal Network for Joint Sparse-View Reconstruction and Metal Artifact Reduction in CT Images | Hong Wang | [code](https://github.com/hongwang01/MEPNet) |\n| Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer | Mingyuan Meng | [code](https://github.com/MungoMeng/Survival-XSurv) |\n| Mesh2SSM: From Surface Meshes to Statistical Shape Models of Anatomy | Krithika Iyer | [code](https://github.com/iyerkrithika21/mesh2SSM_2023/tree/main) |\n| MetaLR: Meta-tuning of Learning Rates for Transfer Learning in Medical Imaging | Yixiong Chen | [code](https://github.com/jannisborn/covid19 ultrasound) |\n| M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization | Che Liu | [code](https://github.com/cheliu-computation/m-flag-miccai2023) |\n| M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient Supervision | Malo Alefsen | [code](https://github.com/MaloADBA/MGenSeg_2D) |\n| Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion Detection | Haojun Yu | [code](https://github.com/HaojunYu1998/UltraDet) |\n| MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization | Yuan Bi | [code](https://github.com/yuan-12138/MI-SegNet) |\n| Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping | Kazuya Nishimura | [code](https://github.com/naivete5656/MDPAFOF) |\n| MixUp-MIL: Novel Data Augmentation for Multiple Instance Learning and a Study on Thyroid Cancer Diagnosis | Michael Gadermayr | [code](https://gitlab.com/mgadermayr/mixupmil) |\n| MoCoSR: Respiratory Motion Correction and Super-Resolution for 3D Abdominal MRI | Weitong Zhang | [code](https://github.com/vito1820/MoCoSR) |\n| Modeling Alzheimers' Disease Progression from Multi-task and Self-supervised Learning Perspective with Brain Networks | Wei Liang | [code](https://github.com/IntelliDAL/Graph/tree/main/SMP-Net) |\n| ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer | Haiqiao Wang | [code](https://github.com/ZAX130/SmileCode) |\n| ModusGraph: Automated 3D and 4D Mesh Model Reconstruction from cine CMR with Improved Accuracy and Efficiency | Yu Deng | [code](https://github.com/MalikTeng/ModusGraph) |\n| Morphology-inspired Unsupervised Gland Segmentation via Selective Semantic Grouping | Qixiang Zhang | [code](https://github.com/xmed-lab/MSSG) |\n| Motion Compensated Unsupervised Deep Learning for 5D MRI | Joseph Kettelkamp | [code](https://github.com/joseph-kettelkamp/5D_MRI) |\n| MPBD-LSTM: A Predictive Model For Colorectal Liver Metastases Using Time Series Multi-phase Contrast-Enhanced CT Scans | Xueyang Li | [code](https://github.com/XueyangLiOSU/MPBD-LSTM) |\n| MRIS: A Multi-modal Retrieval Approach for Image Synthesis on Diverse Modalities | Boqi Chen | [code](https://github.com/uncbiag/MRIS) |\n| MulHiST: Multiple Histological Staining for Thick Biological Samples via Unsupervised Image-to-Image Translation | Lulin Shi | [code](https://github.com/TABLAB-HKUST/MulHiST) |\n| Multi-Head Multi-Loss Model Calibration | Adrian Galdran | [code](https://github.com/agaldran/mhml_calibration) |\n| Multimodal brain age estimation using interpretable adaptive population-graph learning | Kyriaki-Margarita Bintsi | [code](https://github.com/bintsi/adaptive-graph-learning) |\n| Multimodal Deep Fusion in Hyperbolic Space for Mild Cognitive Impairment Study | Lu Zhang | [code](https://github.com/qidianzl/Multimodal-Deep-Fusion-in-Hyperbolic-Space) |\n| Multi-modal Variational Autoencoders for normative modelling across multiple imaging modalities | Ana Lawry Aguila | [code](https://github.com/alawryaguila/multimodal-normative-models) |\n| Multi-modality contrastive learning for sarcopenia screening from hip X-rays and clinical information | Qiangguo Jin | [code](https://github.com/qgking/MM-CL.git) |\n| Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection | Aofan Jiang | [code](https://github.com/MediaBrain-SJTU/ECGAD) |\n| Multi-scope Analysis Driven Hierarchical Graph Transformer for Whole Slide Image based Cancer Survival Prediction | Wentai Hou | [code](https://github.com/Baeksweety/superpixel_transformer) |\n| Multi-shot Prototype Contrastive Learning and Semantic Reasoning for Medical Image Segmentation | Yuhui Song | [code](https://github.com/H51705/FSS_MPSNet) |\n| MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation | Constantin Ulrich | [code](https://github.com/MIC-DKFZ/MultiTalent) |\n| Multi-Target Domain Adaptation with Prompt Learning for Medical Image Segmentation | Yili Lin | [code](https://github.com/MurasakiLin/prompt-DA) |\n| Multi-view Guidance for Self-supervised Monocular Depth Estimation on Laparoscopic Images via Spatio-temporal Correspondence | Wenda Li | [code](https://github.com/MoriLabNU/MGMDepthL) |\n| Multi-View Vertebra Localization and Identification from CT Images | Han Wu | [code](https://github.com/ShanghaiTech-IMPACT/Multi-View-Vertebra-Localization-and-Identification-from-CT-Images) |\n| NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models | Aman Shrivastava | [code](https://github.com/4m4n5/NASDM) |\n| Neural LerPlane Representations for Fast 4D Reconstruction of Deformable Tissues | Chen Yang | [code](https://github.com/Loping151/LerPlane) |\n| Neural Pre-Processing: A Learning Framework for End-to-end Brain MRI Pre-processing | Xinzi He | [code](https://github.com/Novestars/Neural_Pre_Processing) |\n| NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants | Chenyu Xue | [code](https://github.com/ladderlab-xjtu/NeuroExplainer) |\n| NISF: Neural Implicit Segmentation Functions | Nil Stolt-Ans¨® | [code](https://github.com/NILOIDE/Implicit_segmentation) |\n| Non-iterative Coarse-to-fine Transformer Networks for Joint Affine and Deformable Image Registration | Mingyuan Meng | [code](https://github.com/MungoMeng/Registration-NICE-Trans) |\n| On the Relevance of Temporal Features for Medical Ultrasound Video Recognition | D. Hudson Smith | [code](https://github.com/MedAI-Clemson/pda_detection) |\n| One-shot Federated Learning on Medical Data using Knowledge Distillation with Image Synthesis and Client Model Adaptation | Myeongkyun Kang | [code](https://github.com/myeongkyunkang/FedISCA) |\n| One-Shot Traumatic Brain Segmentation with Adversarial Training and Uncertainty Rectification | Xiangyu Zhao | [code](https://github.com/hsiangyuzhao/TBIOneShot) |\n| Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models | Tom van Sonsbeek | [code](https://github.com/tjvsonsbeek/open-ended-medical-vqa) |\n| Optimizing the 3D Plate Shape for Proximal Humerus Fractures | Marilyn Keller | [code](https://github.com/MarilynKeller/HumerusPlate) |\n| Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learning | Zheng Zhang | [code](https://github.com/ZhangZ7112/PVA-CAS) |\n| Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction | Kexin Ding | [code](https://github.com/Cassie07/PathOmics) |\n| PCMC-T1: Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction | Eyal Hanania | [code](https://gith","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJunMa11%2FMICCAI-OpenSourcePapers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FJunMa11%2FMICCAI-OpenSourcePapers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FJunMa11%2FMICCAI-OpenSourcePapers/lists"}