An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.

Journal: Translational vision science & technology
PMID: 37988073

Abstract

PURPOSE: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data.

Authors

  • Jamie Burke
    School of Mathematics, University of Edinburgh, Edinburgh, UK.
  • Justin Engelmann
    School of Informatics, University of Edinburgh, Edinburgh, UK.
  • Charlene Hamid
    Clinical Research Facility and Imaging, University of Edinburgh, Edinburgh, UK.
  • Megan Reid-Schachter
    Clinical Research Facility and Imaging, University of Edinburgh, Edinburgh, UK.
  • Tom Pearson
    University Hospital Wales, NHS Wales, Cardiff, Wales, UK.
  • Dan Pugh
    British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Neeraj Dhaun
    British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK.
  • Amos Storkey
  • Stuart King
    School of Mathematics, University of Edinburgh, Edinburgh, UK.
  • Tom J MacGillivray
    VAMPIRE project, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK.
  • Miguel O Bernabeu
    Usher Institute, University of Edinburgh, UK.
  • Ian J C MacCormick

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