Comprehensive Head and Neck Organs at Risk Segmentation Using Stratified Learning and Neural Architecture Search

We introduced a new stratified method for segmenting a large comprehensive set of H&N OARs. Our method integrates multi-stage segmentation and NAS in a synergy for the first time. It was trained using OPX patients and achieved state-of-the-art performance and generalized well to patients of NPC. Our method is a critical step towards an automated, accurate, and dependable OAR segmentation system in various H&N cancers.