Federated Learning for Microvasculature Segmentation and Diabetic Retinopathy Classification of OCT Data.

Journal: Ophthalmology science
Published Date: Oct 8, 2021

Abstract

PURPOSE: To evaluate the performance of a federated learning framework for deep neural network-based retinal microvasculature segmentation and referable diabetic retinopathy (RDR) classification using OCT and OCT angiography (OCTA).

Authors

  • Julian Lo
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.
  • Timothy T Yu
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.
  • Da Ma
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.
  • Pengxiao Zang
    Casey Eye Institute, Oregon Health and Science University, Portland, Oregon.
  • Julia P Owen
    Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Qinqin Zhang
    Department of Bioengineering, University of Washington, Seattle, Washington.
  • Ruikang K Wang
    Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Mirza Faisal Beg
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.
  • Aaron Y Lee
    Department of Ophthalmology, University of Washington, Seattle, Washington.
  • Yali Jia
    Casey Eye Institute, Oregon Health and Science University, Portland, Oregon.
  • Marinko V Sarunic
    School of Engineering Science, Simon Fraser University, Burnaby, Canada.

Keywords

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