Detection of vertical root fractures by cone-beam computed tomography based on deep learning.

Journal: Dento maxillo facial radiology
PMID: 36802858

Abstract

OBJECTIVES: This study aims to evaluate the performance of ResNet models in the detection of and vertical root fractures (VRF) in Cone-beam Computed Tomography (CBCT) images.

Authors

  • Pan Yang
    Department of Oral and Maxillofacial Radiology, Beijing Stomatology Hospital, School of Stomatology, Capital Medical University, Beijing, China.
  • Xiaolong Guo
    Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, Beijing, China.
  • Chuangchuang Mu
    Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, Beijing, China.
  • Senrong Qi
    Department of Oral and Maxillofacial Radiology, Beijing Stomatology Hospital, School of Stomatology, Capital Medical University, Beijing, China.
  • Gang Li
    The Centre for Cyber Resilience and Trust, Deakin University, Australia.

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