OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications.

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

Abstract

PURPOSE: Intravitreal injections with anti-vascular endothelial growth factor (anti-VEGF) medications have become the standard of care for their respective indications. Optical coherence tomography (OCT) scans of the central retina provide detailed anatomical data and are widely used by clinicians in the decision-making process of anti-VEGF indication. In recent years, significant progress has been made in artificial intelligence and computer vision research. We trained a deep convolutional artificial neural network to predict treatment indication based on central retinal OCT scans without human intervention.

Authors

  • Philipp Prahs
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany. philipp.prahs@ukr.de.
  • Viola Radeck
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany.
  • Christian Mayer
    Department of Ophthalmology, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
  • Yordan Cvetkov
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany.
  • Nadezhda Cvetkova
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany.
  • Horst Helbig
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany.
  • David Märker
    Department of Ophthalmology, University of Regensburg, Franz-Josef-Strauss-Allee 11, 93042, Regensburg, Germany.