[Potential of methods of artificial intelligence for quality assurance].

Journal: Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft
Published Date: Apr 1, 2020

Abstract

BACKGROUND: Procedures with artificial intelligence (AI), such as deep neural networks, show promising results in automatic analysis of ophthalmological imaging data.

Authors

  • Philipp Berens
    Hertie Institute for AI in Brain Health, University of Tübingen, Tübingen, Germany.
  • Sebastian M Waldstein
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Murat Seckin Ayhan
    Forschungsinstitut für Augenheilkunde, Universität Tübingen, Otfried-Müller-Str. 25, 72076, Tübingen, Deutschland.
  • Louis Kümmerle
    Forschungsinstitut für Augenheilkunde, Universität Tübingen, Otfried-Müller-Str. 25, 72076, Tübingen, Deutschland.
  • Hansjürgen Agostini
    Klinik für Augenheilkunde, Universitätsklinikum Freiburg, Freiburg, Deutschland.
  • Andreas Stahl
    Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany.
  • Focke Ziemssen
    Universitäts-Augenklinik Tübingen, Universität Tübingen, Tübingen, Deutschland.

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