Analyzing Tumors by Synthesis

no code implementations • 9 Sep 2024 • Qi Chen, Yuxiang Lai, Xiaoxi Chen, Qixin Hu, Alan Yuille, Zongwei Zhou

We also present case studies in the liver, pancreas, and kidneys reveal that AI trained on synthetic tumors can achieve performance comparable to, or better than, AI only trained on real data.

AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarking

2 code implementations • 23 Jul 2024 • Wenxuan Li, Chongyu Qu, Xiaoxi Chen, Pedro R. A. S. Bassi, Yijia Shi, Yuxiang Lai, Qian Yu, Huimin Xue, Yixiong Chen, Xiaorui Lin, Yutong Tang, Yining Cao, Haoqi Han, Zheyuan Zhang, Jiawei Liu, Tiezheng Zhang, Yujiu Ma, Jincheng Wang, Guang Zhang, Alan Yuille, Zongwei Zhou

AbdomenAtlas provides 673K high-quality masks of anatomical structures in the abdominal region annotated by a team of 10 radiologists with the help of AI algorithms.

Benchmarking Transfer Learning

From Pixel to Cancer: Cellular Automata in Computed Tomography

1 code implementation • 11 Mar 2024 • Yuxiang Lai, Xiaoxi Chen, Angtian Wang, Alan Yuille, Zongwei Zhou

We apply these three generic rules to simulate tumor development--from pixel to cancer--using cellular automata.

Computed Tomography (CT)

Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation

no code implementations • 9 Oct 2023 • Yuxiang Lai, Yi Zhou, Xinghong Liu, Tao Zhou

To address these issues, we propose a novel Memory-Assisted Sub-Prototype Mining (MemSPM) method that can learn the differences between samples belonging to the same category and mine sub-classes when there exists significant concept shift between them.

Universal Domain Adaptation