KeratoScreen: Early Keratoconus Classification With Zernike Polynomial Using Deep Learning.

Journal: Cornea
Published Date: Sep 1, 2022

Abstract

PURPOSE: We aimed to investigate the usefulness of Zernike coefficients (ZCs) for distinguishing subclinical keratoconus (KC) from normal corneas and to evaluate the goodness of detection of the entire corneal topography and tomography characteristics with ZCs as a screening feature input set of artificial neural networks.

Authors

  • He-Bei Gao
    Division of Health Sciences, Hangzhou Normal University, Hangzhou, China.
  • Zhi-Geng Pan
    School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing, China.
  • Mei-Xiao Shen
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, China ; and.
  • Fan Lü
    Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
  • Hong Li
    Department of Public Health Sciences, Medical College of South Carolina, Charleston, SC.
  • Xiao-Qin Zhang
    College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, China .

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