A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.

Background And Purpose: Delineating organs at risk (OARs) on computed tomography (CT) images is an essential step in radiation therapy; however, it is notoriously time-consuming and prone to inter-observer variation. Herein, we report a deep learning-based automatic segmentation (AS) algorithm (WBNet) that can accurately and efficiently delineate all major OARs in the entire body directly on CT scans.

Materials And Methods: We collected 755 CT scans of the head and neck, thorax, abdomen, and pelvis and manually delineated 50 OARs on the CT images.