4k citations · 16.1k across the 265 of their papers we have counts for
20 papers · 1 filter
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Bowen Li, Yu-Cheng Chou, Shuwen Sun +3
Early detection and localization of pancreatic cancer can increase the 5-year survival rate for patients from 8.5% to 20%. Artificial intelligence (AI) can potentially assist radio…
Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
Yixiao Zhang, Xinyi Li, Huimiao Chen +3
The ability to dynamically extend a model to new data and classes is critical for multiple organ and tumor segmentation. However, due to privacy regulations, accessing previous dat…
AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
Chongyu Qu, Tiezheng Zhang, Hualin Qiao +4
Annotating medical images, particularly for organ segmentation, is laborious and time-consuming. For example, annotating an abdominal organ requires an estimated rate of 30-60 minu…
Label-Free Liver Tumor Segmentation
Qixin Hu, Yixiong Chen, Junfei Xiao +4
We demonstrate that AI models can accurately segment liver tumors without the need for manual annotation by using synthetic tumors in CT scans. Our synthetic tumors have two intrig…
CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Jieneng Chen, Yingda Xia, Jiawen Yao +22
Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus o…
CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
Jie Liu, Yixiao Zhang, Jie-Neng Chen +7
An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem…