Utility of deep learning for the diagnosis of cochlear malformation on temporal bone CT.

Journal: Japanese journal of radiology
PMID: 37812304

Abstract

OBJECTIVE: Diagnosis of cochlear malformation on temporal bone CT images is often difficult. Our aim was to assess the utility of deep learning analysis in diagnosing cochlear malformation on temporal bone CT images.

Authors

  • Zhenhua Li
    Affiliated Hospital of Changchun University of Chinese Medicine, 1035 Boshuo Road, Changchun, 130117, Jilin, China. 19390078790@163.com.
  • Langtao Zhou
    School of Cyberspace Security, Guangzhou University, Guangzhou, China.
  • Xiang Bin
    Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
  • Songhua Tan
    Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China.
  • Zhiqiang Tan
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System, Shenzhen 518055, China; University of Chinese Academy of Sciences, CAS, Beijing 100049, China. Electronic address: zq.tan@siat.ac.cn.
  • Anzhou Tang
    Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China. tanganzhou@gxmu.edu.cn.

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