An Automatic Image Processing System for Glaucoma Screening

Joint Authors

Almazroa, Ahmed
Lakshminarayanan, Vasudevan
Alodhayb, Sami
Raahemifar, Kaamran

Source

International Journal of Biomedical Imaging

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-19, 19 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-08-29

Country of Publication

Egypt

No. of Pages

19

Main Subjects

Medicine

Abstract EN

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.

American Psychological Association (APA)

Almazroa, Ahmed& Alodhayb, Sami& Raahemifar, Kaamran& Lakshminarayanan, Vasudevan. 2017. An Automatic Image Processing System for Glaucoma Screening. International Journal of Biomedical Imaging،Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1159664

Modern Language Association (MLA)

Almazroa, Ahmed…[et al.]. An Automatic Image Processing System for Glaucoma Screening. International Journal of Biomedical Imaging No. 2017 (2017), pp.1-19.
https://search.emarefa.net/detail/BIM-1159664

American Medical Association (AMA)

Almazroa, Ahmed& Alodhayb, Sami& Raahemifar, Kaamran& Lakshminarayanan, Vasudevan. An Automatic Image Processing System for Glaucoma Screening. International Journal of Biomedical Imaging. 2017. Vol. 2017, no. 2017, pp.1-19.
https://search.emarefa.net/detail/BIM-1159664

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1159664