Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration.

Journal: Acta ophthalmologica
Published Date: Nov 26, 2019

Abstract

PURPOSE: To validate the performance of a commercially available, CE-certified deep learning (DL) system, RetCAD v.1.3.0 (Thirona, Nijmegen, The Netherlands), for the joint automatic detection of diabetic retinopathy (DR) and age-related macular degeneration (AMD) in colour fundus (CF) images on a dataset with mixed presence of eye diseases.

Authors

  • Cristina González-Gonzalo
    A-eye Research Group, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Verónica Sánchez-Gutiérrez
    Department of Ophthalmology, University Hospital Ramón y Cajal, Ramón y Cajal Health Research Institute (IRYCIS), Madrid, Spain.
  • Paula Hernández-Martínez
    Department of Ophthalmology, University Hospital Ramón y Cajal, Ramón y Cajal Health Research Institute (IRYCIS), Madrid, Spain.
  • Inés Contreras
    Department of Ophthalmology, University Hospital Ramón y Cajal, Ramón y Cajal Health Research Institute (IRYCIS), Madrid, Spain.
  • Yara T Lechanteur
    Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Artin Domanian
    Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Bram van Ginneken
    Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer Mevis, Bremen, Germany.
  • Clara I Sanchez

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