Deep learning model to predict visual field in central 10° from optical coherence tomography measurement in glaucoma.

Journal: The British journal of ophthalmology
Published Date:

Abstract

BACKGROUND/AIM: To train and validate the prediction performance of the deep learning (DL) model to predict visual field (VF) in central 10° from spectral domain optical coherence tomography (SD-OCT).

Authors

  • Yohei Hashimoto
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
  • Ryo Asaoka
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
  • Taichi Kiwaki
    Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
  • Hiroki Sugiura
    Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.
  • Shotaro Asano
    Department of Ophthalmology, Graduate School of Medicine and Faculty of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan.
  • Hiroshi Murata
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
  • Yuri Fujino
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
  • Masato Matsuura
    Department of Ophthalmology, The University of Tokyo, Tokyo, Japan; Moorfields Eye Hospital National Health Service Foundation Trust and University College London, Institute of Ophthalmology, London, United Kingdom.
  • Atsuya Miki
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Kazuhiko Mori
    Medicinal Safety Research Laboratories, Daiichi Sankyo Co., Ltd., 1-16-13 Kitakasai, Edogawa-ku, Tokyo, 134-8630, Japan.
  • Yoko Ikeda
    Department of Ophthalmology, Kyoto Prefectural University of Medicine, Kyoto, Japan; Oike Ikeda Eye Clinic, Kyoto, Japan.
  • Takashi Kanamoto
    Department of Ophthalmology, Hiroshima Memorial Hospital, Hiroshima, Japan.
  • Junkichi Yamagami
    JR Tokyo General Hospital, Tokyo, Japan.
  • Kenji Inoue
    Inouye Eye Hospital, Tokyo, Japan.
  • Masaki Tanito
    Division of Ophthalmology, Matsue Red Cross Hospital, Shimane, Japan.
  • Kenji Yamanishi
    Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.