Stars
MedSAM3: Delving into Segment Anything with Medical Concepts
[ICLR 2024 Oral] Supervised Pre-Trained 3D Models for Medical Image Analysis (9,262 CT volumes + 25 annotated classes)
[MICCAI 2025 Best Paper Award Runner-up] Learning Segmentation from Radiology Reports
Improved tumor synthesis leveraging radiology reports as prompts for diffusion models.
MedSAM2: Segment Anything in 3D Medical Images and Videos
A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding
[MICCAI 2021] You Only Learn Once: Universal Anatomical Landmark Detection https://arxiv.org/abs/2103.04657
An MRI-pathology model (MRI-based Predicted Transformer for Prostate cancer (MRI-PTPCa)) was proposed to discover correlations between mp-MRI and tumor regressiveness of PCa and was further deploye…
MedDINOv3: How to adapt vision foundation models for medical image segmentation?
[MedIA 2025] CLIK-Diffusion: Clinical Knowledge-informed Diffusion Model for Tooth Alignment
Soft Masked Mamba Diffusion Model for CT to MRI Conversion (Official PyTorch Implementation)
Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)
[NeurIPS 2025] PanTS: The Pancreatic Tumor Segmentation Dataset
Repo for MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images
[IEEE TMI 2025] 3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-quality Medical Image Generation
A foundation model for universal 3D blood vessel segmentation. Paper accepted @ CVPR25.
DeepPrep: An accelerated, scalable, and robust pipeline for neuroimaging preprocessing empowered by deep learning
A codebase and a curated list of awesome deep long-tailed learning (TPAMI 2023).
PyTorch implementation of MoCo v3 https//arxiv.org/abs/2104.02057
Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology (ICLR 2025)