Deep learning-based evaluation of the relationship between mandibular third molar and mandibular canal on CBCT.

Journal: Clinical oral investigations
PMID: 34312683

Abstract

OBJECTIVES: The objective of our study was to develop and validate a deep learning approach based on convolutional neural networks (CNNs) for automatic detection of the mandibular third molar (M3) and the mandibular canal (MC) and evaluation of the relationship between them on CBCT.

Authors

  • Mu-Qing Liu
    Center for TMD and Orofacial Pain, Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, No. 22 Zhong Guan Cun South Ave, Beijing, 100081, People's Republic of China.
  • Zi-Neng Xu
    Deepcare, Inc, Beijing, China.
  • Wei-Yu Mao
    Center for TMD and Orofacial Pain, Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, No. 22 Zhong Guan Cun South Ave, Beijing, 100081, People's Republic of China.
  • Yuan Li
    NHC Key Lab of Hormones and Development and Tianjin Key Lab of Metabolic Diseases, Tianjin Medical University Chu Hsien-I Memorial Hospital & Institute of Endocrinology, Tianjin, China.
  • Xiao-Han Zhang
    Center for TMD and Orofacial Pain, Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, No. 22 Zhong Guan Cun South Ave, Beijing, 100081, People's Republic of China.
  • Hai-Long Bai
    Deepcare, Inc, Beijing, China.
  • Peng Ding
    Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China.
  • Kai-Yuan Fu
    Center for TMD and Orofacial Pain, Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology, No. 22 Zhong Guan Cun South Ave, Beijing, 100081, People's Republic of China. kqkyfu@bjmu.edu.cn.

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