Year: 2025
Type: conference-paper
Abstract: Accurate anatomical labeling of abdominal arteries plays a pivotal role in diagnosing abdominal vascular diseases. But existing methods have certain limitations, such as insufficient focus on global correlations and an over-reliance on prior knowledge. In this study, multiple branches of the abdominal aorta are grouped into a single hyperedge, and a hypergraph neural network (HGNN) is employed to extract branch geometric features, spatial features, and topological encoding features obtained through dual branch traversals. Experiments are conducted on the public dataset TotalSegmentator. The experimental results show that our method can achieve the best results on the main branch Ao and branches at all levels.
Authors: Yuehai Wang, Yuchen Guo, Na Xing
Institutions: North China University of Technology, Beijing Open University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411887371