Automatic segmentation and visualization of cortical and marrow bone in mandibular condyle on CBCT: a preliminary exploration of clinical application.

Objectives: To develop a deep learning-based automatic segmentation method for cortex and marrow in mandibular condyle on cone-beam computed tomography (CBCT) images and explore its clinical application.

Methods: 825 condyles of 490 CBCT images from 3 centers of Stomatology hospital affliated to Zhejiang University School of Medicine were collected. A deep learning model was developed for simultaneous segmentation of cortex and marrow in mandibular condyle.