Diagnosis of Choroidal Disease With Deep Learning-Based Image Enhancement and Volumetric Quantification of Optical Coherence Tomography.

Journal: Translational vision science & technology
Published Date: Jan 3, 2022

Abstract

PURPOSE: The purpose of this study was to quantify choroidal vessels (CVs) in pathological eyes in three dimensions (3D) using optical coherence tomography (OCT) and a deep-learning analysis.

Authors

  • Kazuichi Maruyama
    Department of Vision Informatics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Song Mei
    Topcon Advanced Biomedical Imaging Laboratory, Oakland, New Jersey, USA.
  • Hirokazu Sakaguchi
    Department of Advanced Device Medicine, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Chikako Hara
    Department of Advanced Device Medicine, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Atsuya Miki
    Department of Ophthalmology, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Zaixing Mao
    Topcon Advanced Biomedical Imaging Laboratory, Oakland, New Jersey, USA.
  • Ryo Kawasaki
    Department of Vision Informatics, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Zhenguo Wang
    Topcon Advanced Biomedical Imaging Laboratory, Oakland, New Jersey, USA.
  • Susumu Sakimoto
    Department of Ophthalmology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Noriyasu Hashida
    Department of Ophthalmology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.
  • Andrew J Quantock
    Structural Biophysics Group, School of Optometry and Vision Sciences, Cardiff University, Cardiff, Wales, UK.
  • Kinpui Chan
    Topcon Advanced Biomedical Imaging Laboratory, Oakland, New Jersey, USA.
  • Kohji Nishida
    Department of Ophthalmology, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.

Keywords

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