Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

Abstract

Authors

• Ryo Asaoka
  Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
• Masaki Tanito
  Division of Ophthalmology, Matsue Red Cross Hospital, Shimane, Japan.
• Naoto Shibata
  Queue inc, Tokyo, Japan.
• Keita Mitsuhashi
  Queue inc, Tokyo, Japan.
• Kenichi Nakahara
  Queue Inc., 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.
• Hiroshi Murata
  Department of Ophthalmology, The University of Tokyo, Tokyo, Japan.
• Kana Tokumo
  Department of Ophthalmology and Visual Science, Hiroshima University, Hiroshima, Japan.
• Yoshiaki Kiuchi
  Department of Ophthalmology and Visual Sciences, Graduate School of Biomedical Sciences, Hiroshima University, 1-2-3 Minami, Kasumi, Hioroshima, 734-8553, Japan.

Keywords

External Resources