Automatic jawbone structure segmentation on dental CBCT images via deep learning.

Journal: Clinical oral investigations
PMID: 39604672

Abstract

OBJECTIVES: This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone on cone beam computed tomography (CBCT) images.

Authors

  • Yuan Tian
    Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Jin Hao
  • Mingzheng Wang
    Angelalign Technology Inc., No. 500 Zhengli Road, Yangpu District, Shanghai, 200433, China.
  • Zhejia Zhang
    Angelalign Technology Inc., No. 500 Zhengli Road, Yangpu District, Shanghai, 200433, China.
  • Ge Wang
    Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, New York, USA.
  • Dazhi Kou
    Shanghai Supercomputer Center, No. 585 Guoshoujing Road, Pudong New District, Shanghai, 201203, China.
  • Lichao Liu
    Angelalign Technology Inc., No. 500 Zhengli Road, Yangpu District, Shanghai, 200433, China.
  • Xiaolin Liu
    Department of Physics, Shanghai University of Electric Power, Shanghai 200090, China. Electronic address: xlliu@shiep.edu.cn.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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