Deep Learning Using Preoperative AS-OCT Predicts Graft Detachment in DMEK.

Journal: Translational vision science & technology
PMID: 37184500

Abstract

PURPOSE: To evaluate a novel deep learning algorithm to distinguish between eyes that may or may not have a graft detachment based on pre-Descemet membrane endothelial keratoplasty (DMEK) anterior segment optical coherence tomography (AS-OCT) images.

Authors

  • Alastair Patefield
    Department of Eye and Vision Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
  • Yanda Meng
    Department of Computer Science, University of Exeter, Exeter, United Kingdom.
  • Matteo Airaldi
    Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
  • Giulia Coco
    Department of Clinical Sciences and Translational Medicine, University of Rome Tor Vergata, Rome, Italy.
  • Sabrina Vaccaro
    Department of Corneal Diseases, St. Paul's Eye Unit, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
  • Mohit Parekh
    Schepens Eye Research Institute, Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, Boston, MA, USA.
  • Francesco Semeraro
    Ophthalmology Clinic, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy.
  • Kunal A Gadhvi
    Department of Eye and Vision Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
  • Stephen B Kaye
    Department of Eye and Vision Sciences, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK.
  • Yalin Zheng
    Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom.
  • Vito Romano
    Department of Eye and Vision Science, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.

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