Keratoconus Screening Based on Deep Learning Approach of Corneal Topography.

Journal: Translational vision science & technology
Published Date: Sep 1, 2020

Abstract

PURPOSE: To develop and compare deep learning (DL) algorithms to detect keratoconus on the basis of corneal topography and validate with visualization methods.

Authors

  • Bo-I Kuo
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Wen-Yi Chang
    National Center for High-Performance Computing, National Applied Research Laboratories, Hsinchu, Taiwan.
  • Tai-Shan Liao
    Taiwan Instrument Research Institute, National Applied Research Laboratories, Hsinchu, Taiwan.
  • Fang-Yu Liu
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Hsin-Yu Liu
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Hsiao-Sang Chu
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Wei-Li Chen
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Fung-Rong Hu
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Jia-Yush Yen
    Department of Mechanical Engineering, National Taiwan University, Taipei, Taiwan.
  • I-Jong Wang
    Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.

Keywords

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