OCT Signal Enhancement with Deep Learning.

Journal: Ophthalmology. Glaucoma
PMID: 33069883

Abstract

PURPOSE: To establish whether deep learning methods are able to improve the signal-to-noise ratio of time-domain (TD) OCT images to approach that of spectral-domain (SD) OCT images.

Authors

  • Georgios Lazaridis
    NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom. Electronic address: g.lazaridis@ucl.ac.uk.
  • Marco Lorenzi
    Epione Research Project, Centre Inria Sophia Antipolis - Méditerranée, Université Côte d'Azur, Valbonne, Antibes, France.
  • Jibran Mohamed-Noriega
    NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom; Departamento de Oftalmología, Hospital Universitario, UANL, Monterrey, México.
  • Soledad Aguilar-Munoa
    NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.
  • Katsuyoshi Suzuki
    Department of Ophthalmology, Yamaguchi University Graduate School of Medicine, Yamaguchi, 755-0046, Japan.
  • Hiroki Nomoto
    NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.
  • Sébastien Ourselin
    Wellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, UK.
  • David F Garway-Heath
    NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom.

Keywords

External Resources

Popular Topics
Recent Journals