Machine learning applied to retinal image processing for glaucoma detection: review and perspective.

Journal: Biomedical engineering online
Published Date: Apr 15, 2020

Abstract

INTRODUCTION: This is a systematic review on the main algorithms using machine learning (ML) in retinal image processing for glaucoma diagnosis and detection. ML has proven to be a significant tool for the development of computer aided technology. Furthermore, secondary research has been widely conducted over the years for ophthalmologists. Such aspects indicate the importance of ML in the context of retinal image processing.

Authors

  • Daniele M S Barros
    Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil. daniele.barros@lais.huol.ufrn.br.
  • Julio C C Moura
    Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.
  • Cefas R Freire
    Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.
  • Alexandre C Taleb
    Federal University of Goias, Goiania, Brazil.
  • Ricardo A M Valentim
    Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.
  • Philippi S G Morais
    Laboratory of Technological Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil.

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