Anomaly Detection in Retinal OCT Images With Deep Learning-Based Knowledge Distillation.

Journal: Translational vision science & technology
PMID: 40146150

Abstract

PURPOSE: The purpose of this study was to develop a robust and general purpose artificial intelligence (AI) system that allows the identification of retinal optical coherence tomography (OCT) volumes with pathomorphological manifestations not present in normal eyes in screening programs and large retrospective studies.

Authors

  • Guilherme Aresta
    Faculdade de Engenharia da Universidade do Porto (FEUP), R. Dr. Roberto Frias s/n, 4200-465 Porto, Portugal.
  • Teresa Araújo
    Faculdade de Engenharia da Universidade do Porto (FEUP), R. Dr. Roberto Frias s/n, 4200-465 Porto, Portugal.
  • 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.

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