Glaucoma management in the era of artificial intelligence.

Journal: The British journal of ophthalmology
Published Date:

Abstract

Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature makes it difficult to diagnose until a late stage. The diagnosis of glaucoma is a complicated and expensive effort that is heavily dependent on the experience and expertise of a clinician. The application of artificial intelligence (AI) algorithms in ophthalmology has improved our understanding of many retinal, macular, choroidal and corneal pathologies. With the advent of deep learning, a number of tools for the classification, segmentation and enhancement of ocular images have been developed. Over the years, several AI techniques have been proposed to help detect glaucoma by analysis of functional and/or structural evaluations of the eye. Moreover, the use of AI has also been explored to improve the reliability of ascribing disease prognosis. This review summarises the role of AI in the diagnosis and prognosis of glaucoma, discusses the advantages and challenges of using AI systems in clinics and predicts likely areas of future progress.

Authors

  • Sripad Krishna Devalla
    Ophthalmic Engineering and Innovation Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore.
  • Zhang Liang
    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
  • Tan Hung Pham
    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
  • Craig Boote
    Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
  • Nicholas G Strouthidis
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Alexandre H Thiéry
    Department of Statistics and Applied Probability, National University of Singapore, Singapore.
  • Michaël J A Girard
    Ophthalmic Engineering and Innovation Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore.