Deep learning segmentation of mandible with lower dentition from cone beam CT.

Journal: Oral radiology
PMID: 39141154

Abstract

OBJECTIVES: This study aimed to train a 3D U-Net convolutional neural network (CNN) for mandible and lower dentition segmentation from cone-beam computed tomography (CBCT) scans.

Authors

  • Daniel C Kargilis
    Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, MD, 21287, United States of America.
  • Winnie Xu
    University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
  • Samir Reddy
    University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
  • Shilpa Shree Kuduva Ramesh
    University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
  • Steven Wang
    University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
  • Anh D Le
    University of Pennsylvania, 1 Founders Pavilion, 3400 Spruce Street, Philadelphia, PA, 19104-4283, USA.
  • Chamith S Rajapakse
    University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.

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