Multi-Resolution Feature Fusion U-Net for Magnetic Resonance Imaging Segmentation

Excerpt

arXiv:2610.00279v1 Announce Type: cross Abstract: The segmentation of anatomical structures in medical images and particularly in MRI scans, is essential for clinical diagnosis and monitoring disease progression. While Deep Learning (DL) architectures, such as U-Net and its extensions are very effective in medical image segmentation tasks, they often struggle with preserving fine-grained details and global contextual information. This is especially challenging for MRI data segmentation, where an