Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters.

Journal: PloS one
Published Date: Dec 19, 2017

Abstract

PURPOSE: This study aimed to develop a machine learning-based algorithm for objective classification of the optic disc in patients with open-angle glaucoma (OAG), using quantitative parameters obtained from ophthalmic examination instruments.

Authors

  • Kazuko Omodaka
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan.
  • Guangzhou An
    R&D Division, TOPCON Corporation, Tokyo, Japan.
  • Satoru Tsuda
    Department of Ophthalmology, Graduate School of Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Yukihiro Shiga
    Department of Ophthalmology, Graduate School of Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Naoko Takada
    Department of Ophthalmology, Graduate School of Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan.
  • Tsutomu Kikawa
    R&D Division, TOPCON Corporation, Tokyo, Japan.
  • Hidetoshi Takahashi
    Division of Ophthalmology, Tohoku Medical and Pharmaceutical University, Department of Medicine, Sendai, Japan.
  • Hideo Yokota
    Cloud-Based Eye Disease Diagnosis Joint Research Team, RIKEN, Wako, Japan.
  • Masahiro Akiba
    R&D Division, TOPCON Corporation, Tokyo, Japan.
  • Toru Nakazawa
    Department of Ophthalmology, Tohoku University Graduate School of Medicine, Miyagi, Japan.

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