Automatic segmentation of retinal images for glaucoma screening

Jun Cheng, Fengshou Yin, Damon Wing Kee Wong, Jiang Liu

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review


Glaucoma is a chronic eye disease in which the optic nerve is progressively damaged. As the disease often progresses silently without symptoms, early detection of glaucoma via screening is important. Cup to disc ratio (CDR) computed from monocular retinal fundus images may provide an option for low cost large-scale glaucoma screening programme. In the chapter, we introduce the Automatic RetinA cup to disc Ratio AssessmenT (ARARAT) system for glaucoma screening. ARARAT uses superpixel classification to segment the optic disc and optic cup from monocular retinal fundus images and computes the CDR values for the screening. The method is validated using two data sets from different races. The areas under curve of the receiver operating characteristic curves are 0.827 and 0.822 from the two data sets. From the discussion with clinicians, the results are promising for large-scale glaucoma screening.

Original languageEnglish
Title of host publicationFrontiers of Medical Imaging
PublisherWorld Scientific Publishing Co.
Number of pages22
ISBN (Electronic)9789814611107
ISBN (Print)9789814611091
Publication statusPublished - 1 Jan 2014
Externally publishedYes

ASJC Scopus subject areas

  • General Biochemistry,Genetics and Molecular Biology
  • General Engineering
  • General Medicine


Dive into the research topics of 'Automatic segmentation of retinal images for glaucoma screening'. Together they form a unique fingerprint.

Cite this