Deep Learning for Automated Sorting of Retinal Photographs.

Journal: Ophthalmology. Retina
Published Date: Mar 17, 2020

Abstract

PURPOSE: Though the domain of big data and artificial intelligence in health care continues to evolve, there is a lack of systemic methods to improve data quality and streamline the preparation process. To address this, we aimed to develop an automated sorting system (RetiSort) that accurately labels the type and laterality of retinal photographs.

Authors

  • Tyler Hyungtaek Rim
    Department of Ocular Epidemiology, Singapore Eye Research Institute, Singapore, Singapore.
  • Zhi Da Soh
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Yih-Chung Tham
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore.
  • Henrik Hee Seung Yang
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Geunyoung Lee
    MediWhale, Seoul, South Korea.
  • Youngnam Kim
    Medi Whale Inc., Seoul, South Korea.
  • Simon Nusinovici
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Daniel Shu Wei Ting
    Singapore National Eye Center, Singapore Eye Research Institute Singapore Health Service Singapore Singapore.
  • Tien Yin Wong
    Singapore National Eye Center, Duke-National University of Singapore Medical School, Singapore 168751, Singapore; National Institutes of Health Research Biomedical Research Centre Biomedical Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
  • Ching-Yu Cheng
    Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore.

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