SOURCE-LINKED INTELLIGENCE

Feature Reconfiguration With Visual Prior for Medical Lesion Segmentation

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Lesion segmentation in medical images plays a critical role in clinical diagnosis and treatment planning. Despite significant advances, lesion segmentation remains challenging due to two major factors: (1) complex background interference; (2) diverse lesion morphology. Existing encoder-decoder based methods mainly focus on enhancing feature extraction or redesigning decoding strategies. However, they lack early prior guidance and feature reconfiguration during the encoding stage, limiting their effectiveness in handling these challenges. To address these limitations, we propose FreNet, a featu

Read original source ↗ Open in workspace

recordType

paper

region

Global