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Digital Image Analysis Of Eye Fundus Images

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ABSTRACT: Digital image analysis of eye fundus images has several benefits than current observer based techniques. The characteristic symptoms of different systemic diseases like hypertension, glaucoma, diabetes and cardiovascular disorder etc. affects retinal vessels. Diseases like diabetes show abnormalities and diameter changes in retinal blood vessels. In hypertension retinal blood vessels show dilatation and elongation of main arteries and veins. Arteriolar to venular diameter ratio (AVR) express high blood pressure levels, diabetic retinopathy and retinopathy of prematurity. Among other image processing operations the estimation of AVR requires vessel segmentation, accurate vessel width measurement and artery or vein classification[1]. Hence the identification of arteries is essential to detect eye diseases. The work has been done on automated classification of retinal vessels and hence it is a challenging task. Nowadays for image analysis graph based methods have been used which are useful for retinal vessel segmentation,retinal image registration and retinal vessel classification[2]. The segmented vessels are analyzed using type of intersection and then assigned artery or vein labels to each vessel segment. So the combination of labels and intensity features decides final artery or vein class.
INTRODUCTION
Most of the methods uses intensity features to differentiate

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