Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation

ArXi:2510.20933v2 Announce Type: replace-cross Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monitoring because it provides precise morphological and spatial information on anatomical structures that directly influence treatment decisions. Convolutional neural networks significantly impact image segmentation; however, since convolution operations are local, capturing global contextual information and long-range dependencies is still challenging.