Segmenting multi-modal abdominal multi-organ using the CADSTransN-Net model

BACKGROUND: , and Relative Volumetric Difference (RVD) of 1.53%. These metrics confirm its high accuracy in region overlap, boundary consistency, and volume estimation for multi-modal abdominal multi-organ segmentation.ConclusionsCADSTransN-Net effectively meets AMOS22's challenges, delivering robust performance across region, boundary, and volume metrics. It provides a reliable solution for multi-modal abdominal multi-organ segmentation, with significant clinical potential for tasks such as surgical navigation.