Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images.

Journal: BMJ open ophthalmology
PMID: 39837590

Abstract

PURPOSE: To develop an artificial intelligence algorithm to automatically identify the anterior segment structures and assess multiple parameters of primary angle closure disease (PACD) in ultrasound biomicroscopy (UBM) images.

Authors

  • Fangting Li
    Department of Ophthalmology, Peking University People's Hospital, Beijing, China.
  • Xiaoyue Zhang
    Ping An Healthcare Technology, Beijing, China.
  • Kangyi Yang
    Department of Ophthalmology, Peking University People's Hospital, Beijing, China.
  • Jiayin Qin
    Department of Ophthalmology, Peking University International Hospital, Beijing, China.
  • Bin Lv
    Ping An Healthcare Technology, Shang Hai, PR China.
  • Kun Lv
    Departments of1Radiology and.
  • Yao Ma
    Student Brigade of Basic Medicine School, Fourth Military Medical University, Xi'an, China.
  • Xingzhi Sun
    Ping An Health Technology, Beijing, China.
  • Yuan Ni
    IBM Research, China, Beijing, China.
  • Guotong Xie
    Ping An Health Technology, Beijing, China.
  • Huijuan Wu
    Beijing Laboratory Animal Research Center, Beijing 100012, PR China. Electronic address: sunnywhj@126.com.

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