Computer-aided diagnosis of glaucoma using fundus images: A review

Yuki Hagiwara, Joel En Wei Koh, Jen Hong Tan, Sulatha V. Bhandary, Augustinus Laude, Edward J. Ciaccio, Louis Tong, U. Rajendra Acharya

Research output: Contribution to journalReview article

23 Citations (Scopus)

Abstract

Background and objectives: Glaucoma is an eye condition which leads to permanent blindness when the disease progresses to an advanced stage. It occurs due to inappropriate intraocular pressure within the eye, resulting in damage to the optic nerve. Glaucoma does not exhibit any symptoms in its nascent stage and thus, it is important to diagnose early to prevent blindness. Fundus photography is widely used by ophthalmologists to assist in diagnosis of glaucoma and is cost-effective. Methods: The morphological features of the disc that is characteristic of glaucoma are clearly seen in the fundus images. However, manual inspection of the acquired fundus images may be prone to inter-observer variation. Therefore, a computer-aided detection (CAD) system is proposed to make an accurate, reliable and fast diagnosis of glaucoma based on the optic nerve features of fundus imaging. In this paper, we reviewed existing techniques to automatically diagnose glaucoma. Results: The use of CAD is very effective in the diagnosis of glaucoma and can assist the clinicians to alleviate their workload significantly. We have also discussed the advantages of employing state-of-art techniques, including deep learning (DL), when developing the automated system. The DL methods are effective in glaucoma diagnosis. Conclusions: Novel DL algorithms with big data availability are required to develop a reliable CAD system. Such techniques can be employed to diagnose other eye diseases accurately.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalComputer Methods and Programs in Biomedicine
Volume165
DOIs
Publication statusPublished - 01-10-2018

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Health Informatics

Fingerprint Dive into the research topics of 'Computer-aided diagnosis of glaucoma using fundus images: A review'. Together they form a unique fingerprint.

  • Cite this

    Hagiwara, Y., Koh, J. E. W., Tan, J. H., Bhandary, S. V., Laude, A., Ciaccio, E. J., Tong, L., & Acharya, U. R. (2018). Computer-aided diagnosis of glaucoma using fundus images: A review. Computer Methods and Programs in Biomedicine, 165, 1-12. https://doi.org/10.1016/j.cmpb.2018.07.012