Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks.

Journal: The British journal of ophthalmology
Published Date: Apr 1, 2021

Abstract

AIMS: To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tomography (OCT) images.

Authors

  • Zhiyan Xu
    Department of Ophthalmology, Peking Union Medical College Hospital, Dongcheng District, Beijing, China.
  • Weisen Wang
    AI & Media Computing Lab, School of Information, Renmin University of China, Beijing, China.
  • Jingyuan Yang
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
  • Jianchun Zhao
    Vistel AI Lab, Visionary Intelligence Ltd, Beijing, China.
  • Dayong Ding
    Vistel AI Lab, Visionary Intelligence Ltd, Beijing, China.
  • Feng He
    Department of Ophthalmology, Peking Union Medical College Hospital, Dongcheng District, Beijing, China.
  • Di Chen
    Department of Gastroenterology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China. Electronic address: 2389446889@qq.com.
  • Zhikun Yang
    Department of Ophthalmology, Peking Union Medical College Hospital, Dongcheng District, Beijing, China.
  • Xirong Li
    Key Lab of DEKE, Renmin University of China, Beijing, China.
  • Weihong Yu
    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China yuweihongpumch@163.com.
  • Youxin Chen
    Department of Ophthalmology Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences Beijing People's Republic of China.

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