Segmentation of macular neovascularization and leakage in fluorescein angiography images in neovascular age-related macular degeneration using deep learning.

Journal: Eye (London, England)
PMID: 35778604

Abstract

BACKGROUND/OBJECTIVES: We aim to develop an objective fully automated Artificial intelligence (AI) algorithm for MNV lesion size and leakage area segmentation on fluorescein angiography (FA) in patients with neovascular age-related macular degeneration (nAMD).

Authors

  • David Holomcik
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, 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.
  • Bilal Haj Najeeb
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Ursula Schmidt-Erfurth
    Christian Doppler Laboratory for Ophthalmic Image Analysis (OPTIMA), Department of Ophthalmology, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria.
  • Gabor Deak
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.

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