AI RESEARCH
UHR-Net: An Uncertainty-Aware Hypergraph Refinement Network for Medical Image Segmentation
arXiv CS.CV
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ArXi:2604.28095v1 Announce Type: new Accurate lesion segmentation is crucial for clinical diagnosis and treatment planning. However, lesions often resemble surrounding tissues and exhibit ill-defined boundaries, leading to unstable predictions in boundary/transition regions. Moreover, small-lesion cues can be diluted by multi-scale feature extraction, causing under- or over-segmentation. To address these challenges, we propose an Uncertainty-Aware Hypergraph Refinement Network (UHR-Net). First, we