An Automatic Image Processing System for Glaucoma Screening

TitleAn Automatic Image Processing System for Glaucoma Screening
Publication TypeJournal Article
Year of Publication2017
AuthorsAlmoqbel, F., S. Alodhayb, K. Raahemifar, and V. Lakshminarayanan
JournalInternational Journal of Biomedical Imaging
Volume2017
Keywordsalgorithm, Article, Automatic image processing, automation, Crucial parameters, Cup to disc ratios, eye fundus, Eye protection, fundus camera, Fuzzy approach, Glaucoma, human, Image processing, Inpainting techniques, measurement accuracy, ophthalmologist, Ophthalmology, optic disk, optic nerve, Optic nerve head, Optical data processing, retina image, Retinal fundus images, screening, Thresholding
Abstract

Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma's population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm's accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm's accuracy. The algorithm's best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images. © 2017 Ahmed Almazroa et al.

DOI10.1155/2017/4826385