Deep learning assisted retinal microvasculature assessment and cerebral small vessel disease in Fabry disease.

Journal: Orphanet journal of rare diseases
PMID:

Abstract

PURPOSE: The aim of this study was to assess retinal microvascular parameters (RMPs) in Fabry disease (FD) using deep learning, and analyze the correlation with brain lesions related to cerebral small vessel disease (CSVD).

Authors

  • Yingsi Li
    Department of Ophthalmology, Peking University First Hospital, Peking University, Beijing, 100034, China.
  • Xuecong Zhou
    Department of Ophthalmology, Peking University First Hospital, Peking University, Beijing, 100034, China.
  • Junmeng Li
    Department of Ophthalmology, Peking University First Hospital, Beijing, China.
  • Yawen Zhao
    East China University of Political Science and Law, 1575, Wanhangdu Road, Shanghai 200042, PR China; Academy of Forensic Science, 1347, West Guangfu Road, Shanghai 200063, PR China.
  • Yujing Yuan
    Department of Neurology, Peking University First Hospital, Peking University, Beijing, 100034, China.
  • Bo Yang
    Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China.
  • Jingjing Xu
    Visionary Intelligence Ltd., Beijing, China.
  • Qijie Wei
    Vistel AI Lab, Visionary Intelligence Ltd., Beijing, China.
  • Xiaoming Yan
    Department of Ophthalmology, Peking University First Hospital, Peking University, Beijing, 100034, China.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Yuan Wu
    State Key Laboratory of Precision Spectroscopy, Quantum Institute for Light and Atoms, Department of Physics and Electronic Science, East China Normal University, Shanghai 200062, China.