Exploiting texture information in diagnosing Glaucoma

E. T. Gormus*, N. Anantrasirichai, M. Bundy, I. Erchova, N White, J. Fergusson, J Morgan, L. B. Nicholson, A. Achim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

1 Citation (Scopus)


The most common cause of blindness in the world by far is known to be the Glaucoma condition. The increase in the ratio of cup to the disc area and the thinning of retinal layers are the most common symptoms of Glaucoma. Functional and structural features of the eye should be examined in order to distinguish an eye with Glaucoma from a healthy eye. In this study, the texture information in Optical Coherence Tomography (OCT) images, which is one of the functional features is investigated to get the most distinguishing characteristic texture patterns in retina layers. First, sample areas are extracted from 4 main region around the fovea using a systematic approach and calculated the texture features for each area one by one. After this step SVM classifier is exploited to find the features which can impact the diagnosis of Glaucoma condition. This analysis is useful to guide the scientists to diagnose glaucoma where the thickness information is not available or at the beginning of the Glaucoma when thinning is not started yet.

Original languageEnglish
Title of host publication2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Subtitle of host publicationProceedings of a meeting held 15-18 May 2017, Antalya, Turkey
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9781509064946
ISBN (Print)9781509064953
Publication statusPublished - Aug 2017
Event25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Duration: 15 May 201718 May 2017


Conference25th Signal Processing and Communications Applications Conference, SIU 2017

Bibliographical note

Original title in Turkish: Doku Bilgisinin Glokom Hastaliǧinin Teşshis Edilmesinde Kullanilmasi


  • Classification
  • Feature Selection
  • Gloucoma
  • Optical Coherence Tomography (OCT)
  • Support Vector Machines (SVM)
  • Texture Analysis


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