M$^{2}$SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation

ArXi:2303.10894v3 Announce Type: replace Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wise addition or concatenation to fuse different level features progressively in decoder. However, both the two operations easily generate plenty of redundant information, which will weaken the complementarity between different level features, resulting in inaccurate localization and blurred edges of lesions.