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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...
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