Automatic Segmentation in Multiple OCT Layers For Stargardt Disease Characterization Via Deep Learning.

Journal: Translational vision science & technology
Published Date: Apr 1, 2021

Abstract

PURPOSE: This study sought to perform automated segmentation of 11 retinal layers and Stargardt-associated features on spectral-domain optical coherence tomography (SD-OCT) images and to analyze differences between normal eyes and eyes diagnosed with Stargardt disease.

Authors

  • Zubin Mishra
    Doheny Image Analysis Laboratory, Doheny Eye Institute, Los Angeles, CA, USA.
  • Ziyuan Wang
    Doheny Image Analysis Laboratory, Doheny Eye Institute, Los Angeles, CA, USA.
  • SriniVas R Sadda
    Doheny Image Analysis Laboratory, Doheny Eye Institute, Los Angeles, CA, USA.
  • Zhihong Hu
    Department of Pathology and Laboratory Medicine, Hematopathology Section, University of Texas Health Science Center at Houston, Texas, TX, USA.

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