Hyper-reflective foci segmentation in SD-OCT retinal images with diabetic retinopathy using deep convolutional neural networks.

Journal: Medical physics
Published Date: Aug 22, 2019

Abstract

PURPOSE: The purpose of this study was to automatically and accurately segment hyper-reflective foci (HRF) in spectral domain optical coherence tomography (SD-OCT) images with diabetic retinopathy (DR) using deep convolutional neural networks.

Authors

  • Chenchen Yu
    School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
  • Sha Xie
    School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.
  • Sijie Niu
    Shandong Provincial Key Laboratory of Network based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China. Electronic address: sjniu@hotmail.com.
  • Zexuan Ji
    School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China.
  • Wen Fan
    Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Songtao Yuan
    Department of Ophthalmology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Qinghuai Liu
    Department of Ophthalmology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, China.
  • Qiang Chen
    School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China.

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