Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning.

Journal: Acta ophthalmologica
Published Date: Dec 1, 2022

Abstract

PURPOSE: To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomography (AS-OCT): The intraocular lens (IOL), the retrolental space (IOL to the posterior lens capsule) and Berger's space (BS; posterior capsule to the anterior hyaloid membrane).

Authors

  • Luca Schwarzenbacher
    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.
  • Daniel Schartmüller
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Christina Leydolt
    Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
  • Rupert Menapace
    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.

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