RGC-Net: An Automatic Reconstruction and Quantification Algorithm for Retinal Ganglion Cells Based on Deep Learning.

Journal: Translational vision science & technology
Published Date: May 1, 2023

Abstract

PURPOSE: The purpose of this study was to develop a deep learning-based fully automated reconstruction and quantification algorithm which automatically delineates the neurites and somas of retinal ganglion cells (RGCs).

Authors

  • Rui Ma
    Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Lili Hao
    BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
  • Yudong Tao
    Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL, USA.
  • Ximena Mendoza
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
  • Mohamed Khodeiry
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
  • Yuan Liu
    Department of General Surgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
  • Mei-Ling Shyu
    Department of Civil and Mechanical Engineering, School of Science and Engineering, University of Missouri-Kansas City, Kansas City, MO, United States.
  • Richard K Lee
    Department of Urology, Weill Cornell Medical College, New York, NY, USA. ril9010@med.cornell.edu.

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