CRANIOSEG: Deep Learning-Based Automated Segmentation of Craniomaxillofacial Anatomical Structures on Cone-Beam Computed Tomography.
OBJECTIVE To develop and evaluate an nnU-Net v2-based deep-learning model for fully automated multiclass segmentation of 27 craniomaxillofacial anatomical structures on cone-beam computed tomography (CBCT). METHODS This retrospective study included CBCT scans from 106 adult patients. Twenty-seven anatomical structure...