Detection of shallow anterior chamber depth from two-dimensional anterior segment photographs using deep learning.

Journal: BMC ophthalmology
PMID:

Abstract

BACKGROUND: The purpose of this study was to implement and evaluate a deep learning (DL) approach for automatically detecting shallow anterior chamber depth (ACD) from two-dimensional (2D) overview anterior segment photographs.

Authors

  • Zhuyun Qian
    Department of Ophthalmology, Shanghai Aier Eye Hospital, No. 1286, Hongqiao Road, Changning District, Shanghai, 200050, China.
  • Xiaoling Xie
    Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Shantou University Medical College, Shantou, Guangdong, China.
  • Jianlong Yang
    Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, Zhejiang, China.
  • Hongfei Ye
    Department of Ophthalmology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No.1665, Kongjiang Road, Yangpu District, Shanghai, 200092, China.
  • Zhilei Wang
    Department of Ophthalmology, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Jili Chen
    Department of Ophthalmology, Shibei Hospital, Shanghai, China.
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Jianheng Liang
    Aier School of Ophthalmology, Central South University Changsha, Changsha, Hunan Province, China.
  • Lihong Jiang
    Heilongjiang Key Laboratory for Laboratory Animals and Comparative Medicine, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China.
  • Ce Zheng
    Department of Ophthalmology, Shanghai Children's Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Xu Chen
    School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.