A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps.

Journal: Translational vision science & technology
Published Date: Dec 1, 2021

Abstract

PURPOSE: To develop and assess the accuracy of a hybrid deep learning construct for detecting keratoconus (KCN) based on corneal topographic maps.

Authors

  • Ali H Al-Timemy
    Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq.
  • Zahraa M Mosa
    College of Pharmacy, Uruk University, Baghdad, Iraq.
  • Zaid Alyasseri
    Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
  • Alexandru Lavric
    Computers, Electronics and Automation Department, Stefan cel Mare University of Suceava, Suceava 720229, Romania.
  • Marcelo M Lui
    Hospital de Olhos-CRO, Guarulhos, São Paulo, São Paulo, Brazil.
  • Rossen M Hazarbassanov
    Hospital de Olhos-CRO, Guarulhos, São Paulo, São Paulo, Brazil.
  • Siamak Yousefi
    Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.

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