Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology
PMID: 39384413

Abstract

OBJECTIVE: To evaluate the performance of convolutional neural networks (CNNs) for the automated detection and classification of mandibular fractures on multislice spiral computed tomography (MSCT).

Authors

  • Jingjing Mao
    Department of Anesthesiology, Huai'an Hospital Affiliated to Yangzhou University (The Fifth People's Hospital of Huai'an), Huaian, China.
  • Yuhu Du
    College of Computer Science and Engineering, North Minzu University, Yinchuan, P.R. China.
  • Jiawen Xue
    Ningxia Medical University, Ningxia Key Laboratory of Oral Disease Research, Yinchuan, P.R. China.
  • Jingjing Hu
  • Qian Mai
    Department of Stomatology, The First People's Hospital of Yinchuan, Yinchuan, P.R. China.
  • Tao Zhou
    Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Zhongwei Zhou
    Department of Oral and Maxillofacial Surgery, General Hospital of Ningxia Medical University, Yinchuan, P.R. China; Institution of Medical Sciences, General Hospital of Ningxia Medical University, Yinchuan, P.R. China. Electronic address: zzwjoel@hotmail.com.

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