Deep Learning-Assisted Detection of Glaucoma Progression in Spectral-Domain OCT.

Journal: Ophthalmology. Glaucoma
Published Date: Nov 18, 2022

Abstract

PURPOSE: To develop and validate a deep learning (DL) model for detection of glaucoma progression using spectral-domain (SD)-OCT measurements of retinal nerve fiber layer (RNFL) thickness.

Authors

  • Eduardo B Mariottoni
    Vision, Imaging and Performance Laboratory (VIP), Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina, USA.
  • Shounak Datta
    Electronics and Communication Sciences Unit, Indian Statistical Institute, 203, B. T. Road, Kolkata-700 108, India. Electronic address: shounak.jaduniv@gmail.com.
  • Leonardo S Shigueoka
    Vision, Imaging and Performance Laboratory (VIP), Duke Eye Center and Department of Ophthalmology, Duke University, Durham, NC, USA.
  • Alessandro A Jammal
    Vision, Imaging and Performance (VIP) Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina.
  • Ivan M Tavares
    Department of Ophthalmology and Visual Sciences, Paulista School of Medicine, Universidade Federal de Sao Paulo, São Paulo, Brazil.
  • Ricardo Henao
    Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina.
  • Lawrence Carin
    Department of Electronic and Computer Engineering, Duke University, Durham, NC, 27705, USA.
  • Felipe A Medeiros
    Duke Eye Center, Department of Ophthalmology, Duke University, Durham, North Carolina, United States.

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