Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date: Nov 28, 2022

Abstract

PURPOSE: To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.

Authors

  • Ling-Chun Sun
    School of Medicine, National Defense Medical Center, Taipei, Taiwan.
  • Shu-I Pao
    Department of Ophthalmology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan, ROC.
  • Ke-Hao Huang
    Department of Ophthalmology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan, ROC.
  • Chih-Yuan Wei
    Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan.
  • Ke-Feng Lin
    Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei, 106, Taiwan, ROC.
  • Ping-Nan Chen
    Department of Biomedical Engineering, National Defense Medical Center, Taipei, 114, Taiwan, ROC. g931310@gmail.com.

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