A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES.

Journal: Retina (Philadelphia, Pa.)
Published Date:

Abstract

PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.

Authors

  • Dawei Yang
    Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital Fudan University, Shanghai, China.
  • Zihan Sun
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China.
  • Jian Shi
  • Anran Ran
    Department of Ophthalmology and Visual Sciences, the Chinese University of Hong Kong, Hong Kong SAR.
  • Fangyao Tang
  • Ziqi Tang
    Department of Pharmaceutical Chemistry, Department of Bioengineering and Therapeutic Sciences, Institute for Neurodegenerative Diseases, and Bakar Computational Health Sciences Institute, University of California, San Francisco, 675 Nelson Rising Ln Box 0518, San Francisco, CA, 94143, USA.
  • Jerry Lok
    Hong Kong Eye Hospital, Hong Kong SAR.
  • Simon Szeto
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China; Hong Kong Eye Hospital, Hong Kong, China.
  • Jason Chan
    Hong Kong Eye Hospital, Hong Kong SAR.
  • Fanny Yip
    Hong Kong Eye Hospital, Hong Kong SAR.
  • Liang Zhang
  • Qianli Meng
    Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Eye Institute, Guangdong Academy of Medical Sciences, Guangzhou, China; and.
  • Martin Rasmussen
    Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark.
  • Jakob Grauslund
    Department of Ophthalmology, Odense University Hospital, Odense, Denmark; Research Unit of Ophthalmology, Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark; Steno Diabetes Center Odense, Odense, Denmark. Electronic address: jakob.grauslund@rsyd.dk.
  • Carol Y Cheung
    Department of Ophthalmology and Visual Sciences, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. Electronic address: carolcheung@cuhk.edu.hk.