Paper
15 March 2019 Blood vessels quantification to detect glaucoma using retinal fundus images
Fauzia Khan, Sana Sharif, F. M. Ali Khan, Ihtisham Ul Haq
Author Affiliations +
Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110410X (2019) https://doi.org/10.1117/12.2522972
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany
Abstract
Glaucoma is one of the most dangerous causes of blindness that results in permanent blindness within a few years if left untreated. It is very hard to diagnose particularly in early stages. Using ophthalmological images, vasculature of blood vessels is most valuable factor for detecting glaucoma. It can be segmented by image processing techniques which help in early diagnosis. In this research the vasculature found within the optic disc is segmented, then used to calculate its ratio in ISNT quadrants. On the basis of ISNT rule we find out that ratio of blood vessels in each and evaluates the results whether blood vessels are being nasalized i.e. they are violating or obeying ISNT rule. The proposed methodology is examined on 50 images collected from different image databases which are FAU, DMED and MESSIDOR to testify nasalization of vessels in retinal images.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fauzia Khan, Sana Sharif, F. M. Ali Khan, and Ihtisham Ul Haq "Blood vessels quantification to detect glaucoma using retinal fundus images", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110410X (15 March 2019); https://doi.org/10.1117/12.2522972
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Blood vessels

Eye

RGB color model

Databases

Image classification

Algorithm development

Gaussian filters

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