Summarising the retinal vascular calibres in healthy, diabetic and diabetic retinopathy eyes

Leontidis, Georgios and Al-Diri, Bashir and Hunter, Andrew (2016) Summarising the retinal vascular calibres in healthy, diabetic and diabetic retinopathy eyes. Computers in Biology and Medicine, 72 . pp. 65-74. ISSN 0010-4825

Documents
CBM_leontidis_repos_pre.pdf
[img]
[Download]
[img]
Preview
PDF
CBM_leontidis_repos_pre.pdf - Whole Document

8MB
Item Type:Article
Item Status:Live Archive

Abstract

Retinal vessel calibre has been found to be an important biomarker of several retinal diseases, including diabetic retinopathy (DR). Quantifying the retinal vessel calibres is an important step for estimating the central retinal artery and vein equivalents. In this study, an alternative method to the already estab- lished branching coefficient(BC) is proposed for summarising the vessel calibres in retinal junctions. This new method combines the mean diameter ratio with an alternative to Murray’s cube law exponent, derived by the fractal dimen- sion,experimentally, and the branch exponent of cerebral vessels, as has been suggested in previous studies with blood flow modelling. For the above calcu- lations, retinal images from healthy, diabetic and DR subjects were used. In addition, the above method was compared with the BC and was also applied to the evaluation of arteriovenous ratio as a biomarker of progression from diabetes to DR in four consecutive years, i.e. three/two/one years before the onset of DR and the first year of DR. Moreover, the retinal arteries and veins around the optic nerve head were also evaluated. The new approach quantifies the vessels more accurately. The decrease in terms of the mean absolute percentage error was between 0.24% and 0.49%, extending at the same time the quantification beyond healthy subjects.

Keywords:Gamma ratio, diabetic retinopathy, vessel calibres, arteriovenous ratio, Junction exponent, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:22680
Deposited On:05 May 2016 07:02

Repository Staff Only: item control page