Automated OCT angiography image quality assessment using a deep learning algorithm.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date: May 22, 2019

Abstract

PURPOSE: To expedite and to standardize the process of image quality assessment in optical coherence tomography angiography (OCTA) using a specialized deep learning algorithm (DLA).

Authors

  • J L Lauermann
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany.
  • M Treder
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany.
  • M Alnawaiseh
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany.
  • C R Clemens
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany.
  • N Eter
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany.
  • F Alten
    Department of Ophthalmology, University of Muenster Medical Center, Domagkstrasse 15, 48149, Muenster, Germany. florian.alten@ukmuenster.de.

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