CORE: Suppressing Spurious Similarity via Confidence-Aware Prototypes for Few-Shot Medical Image Segmentation.
Few-shot medical image segmentation (FSMIS) aims to segment unseen anatomical structures using only a few annotated examples, alleviating the heavy annotation burden in clinical practice. Most existing FSMIS methods adopt prototype-based learning but suffer from two limitations. First, equal treatment of foreground pix...