Deep learning-based classification of retinal atrophy using fundus autofluorescence imaging.

Journal: Computers in biology and medicine
Published Date: Dec 28, 2020

Abstract

PURPOSE: To automatically classify retinal atrophy according to its etiology, using fundus autofluorescence (FAF) images, using a deep learning model.

Authors

  • Alexandra Miere
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France; Laboratory of Images, Signals and Intelligent Systems (LISSI), (EA N° 3956), University Paris-Est, Créteil, France. Electronic address: alexandra.miere@chicreteil.fr.
  • Vittorio Capuano
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Arthur Kessler
    EPISEN - ISBS, University Paris-Est, Créteil, France.
  • Olivia Zambrowski
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Camille Jung
    Clinical Research Center, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Donato Colantuono
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Carlotta Pallone
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Oudy Semoun
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.
  • Eric Petit
    Laboratory of Images, Signals and Intelligent Systems (LISSI), (EA N° 3956), University Paris-Est, Créteil, France.
  • Eric Souied
    Department of Ophthalmology, Centre Hospitalier Intercommunal de Créteil, Créteil, France.

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