Role of Deep Learning-Quantified Hyperreflective Foci for the Prediction of Geographic Atrophy Progression.

Journal: American journal of ophthalmology
Published Date: Apr 8, 2020

Abstract

PURPOSE: To quantitatively measure hyperreflective foci (HRF) during the progression of geographic atrophy (GA) secondary to age-related macular degeneration (AMD) using deep learning (DL) and investigate the association with local and global growth of GA.

Authors

  • Ursula Schmidt-Erfurth
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Hrvoje Bogunović
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Christoph Grechenig
    Christian Doppler Laboratory for Ophthalmic Image Analysis, Vienna Reading Center, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Patricia Bui
    Christian Doppler Laboratory for Ophthalmic Image Analysis, Vienna Reading Center, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Maria Fabianska
    Christian Doppler Laboratory for Ophthalmic Image Analysis, Vienna Reading Center, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Sebastian Waldstein
    Christian Doppler Laboratory for Ophthalmic Image Analysis, Vienna Reading Center, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Gregor S Reiter
    Department of Ophthalmology and Optometry, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria. gregor.reiter@meduniwien.ac.at.

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