A Mutual Inclusion Mechanism for Precise Boundary Segmentation in Medical Images

no code implementations • 12 Apr 2024 • Yizhi Pan, Junyi Xin, Tianhua Yang, Teeradaj Racharak, Le-Minh Nguyen, Guanqun Sun

Our approach, inspired by radiologists' working patterns, features two distinct modules: (i) \textbf{Mutual Inclusion of Position and Channel Attention (MIPC) module}: To enhance the precision of boundary segmentation in medical images, we introduce the MIPC module, which enhances the focus on channel information when extracting position features and vice versa; (ii) \textbf{GL-MIPC-Residue}: To improve the restoration of medical images, we propose the GL-MIPC-Residue, a global residual connection that enhances the integration of the encoder and decoder by filtering out invalid information and restoring the most effective information lost during the feature extraction process.

Image Segmentation Position +2