[NeurIPS 2023] AbdomenAtlas 1.0 (5,195 CT volumes + 9 annotated classes)
リポジトリ
MrGiovanni のリポジトリ
[CVPR 2017] Official Implementation for AIFT
[NeurIPS 2025] Completeness-Aware Reconstruction Enhancement
Cold Start Problem in Vision Active Learning
[MICCAI 2023] Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
[CVPR 2024] Generalizable Tumor Synthesis - Realistic Synthetic Tumors in Liver, Pancreas, and Kidney
Zongwei Zhou's Ph.D. Dissertation
[ISBI 2023] Official Implementation for Label-Assemble
[ISBI 2025] Design Data Before Models: Using large vision-language models to automatically enhance medical dataset annotations.
Official Keras & PyTorch Implementation and Pre-trained Models for Models Genesis - MICCAI 2019
[MICCAI 2024] Embracing Massive Medical Data
[NeurIPS 2025] PanTS: The Pancreatic Tumor Segmentation Dataset. PanTS is a vision-language dataset, which enables development and external evaluation of AI for pancreatic tumor detection, localization, and reporting, with multi-structure context and metadata to support robust, anatomy-aware modeling.
[MICCAI 2024] Cellular Automata for Tumor Development - Realistic Synthetic Tumors in Liver, Pancreas, and Kidney
[MICCAI 2025 Best Paper Award] Learning Segmentation from Radiology Reports
[ICCV 2025] AbdomenAtlas 3.0 (9,262 CT volumes + medical reports). These “superhuman” reports are more accurate, detailed, standardized, and generated faster than traditional human-made reports.