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Author

Mehmet Uğurlu

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Open access Sep 2026

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...

I. Bayrakdar, Alican Kuran, Mehmet Uğurlu et al. · 0 citations

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