Quality assessment of colour fundus and fluorescein angiography images using deep learning.

Journal: The British journal of ophthalmology
Published Date: Dec 18, 2023

Abstract

BACKGROUND/AIMS: Image quality assessment (IQA) is crucial for both reading centres in clinical studies and routine practice, as only adequate quality allows clinicians to correctly identify diseases and treat patients accordingly. Here we aim to develop a neural network for automated real-time IQA in colour fundus (CF) and fluorescein angiography (FA) images.

Authors

  • Michael König
    Department of Ophthalmology and Optometry, Medical University of Vienna, Wien, Austria.
  • Philipp Seeböck
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Bianca S Gerendas
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Georgios Mylonas
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Rudolf Winklhofer
    Department of Ophthalmology and Optometry, Medical University of Vienna, Wien, Austria.
  • Ioanna Dimakopoulou
    Department of Ophthalmology and Optometry, Medical University of Vienna, Wien, Austria.
  • Ursula Margarethe Schmidt-Erfurth
    Department of Ophthalmology and Optometry, Medical University of Vienna, Wien, Austria ursula.schmidt-erfurth@meduniwien.ac.at.

Keywords

External Resources

Popular Topics
Recent Journals