Diagnosis of central serous chorioretinopathy by deep learning analysis of en face images of choroidal vasculature: A pilot study.

Journal: PloS one
Published Date: Jan 1, 2021

Abstract

PURPOSE: To diagnose central serous chorioretinopathy (CSC) by deep learning (DL) analyses of en face images of the choroidal vasculature obtained by optical coherence tomography (OCT) and to analyze the regions of interest for the DL from heatmaps.

Authors

  • Yukihiro Aoyama
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Ichiro Maruko
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Taizo Kawano
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Tatsuro Yokoyama
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Yuki Ogawa
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Ruka Maruko
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
  • Tomohiro Iida
    Department of Ophthalmology, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.

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