5 papers
OPERA: Offline Policy-guided Expert Routing and Adaptation for Universal Biomedical Image Analysis
Zihan Li, Feiyang Liu, Dandan Shan +2
Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, protocols, and patient population…
Scale-aware Adaptive Supervised Network with Limited Medical Annotations
Zihan Li, Dandan Shan, Yunxiang Li +2
Medical image segmentation faces critical challenges in semi-supervised learning scenarios due to severe annotation scarcity requiring expert radiological knowledge, significant in…
A topology-preserving three-stage framework for fully-connected coronary artery extraction
Yuehui Qiu, Dandan Shan, Yining Wang +5
Coronary artery extraction is a crucial prerequisite for computer-aided diagnosis of coronary artery disease. Accurately extracting the complete coronary tree remains challenging d…
STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation
Dandan Shan, Zihan Li, Yunxiang Li +3
Accurate segmentation of lesions plays a critical role in medical image analysis and diagnosis. Traditional segmentation approaches that rely solely on visual features often strugg…
An Intra- and Cross-frame Topological Consistency Scheme for Semi-supervised Atherosclerotic Coronary Plaque Segmentation
Ziheng Zhang, Zihan Li, Dandan Shan +3
Enhancing the precision of segmenting coronary atherosclerotic plaques from CT Angiography (CTA) images is pivotal for advanced Coronary Atherosclerosis Analysis (CAA), which disti…