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Indian Journal of Public Health Research & Development
Year : 2019, Volume : 10, Issue : 2
First page : ( 1019) Last page : ( 1024)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2019.00430.3

Automated Retinal Imaging System for Detecting Cardiac Abnormalities Using Cup to Disc Ratio

Rajan S. Palanivel1, Kavitha L.2

1Associate Professor, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering (Autonomous), Karur, Tamilnadu, India

2PG Scholar, Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering (Autonomous), Karur, Tamilnadu, India

Online published on 15 March, 2019.

Abstract

This advanced and adaptable world that consists of diseases that are due to the cardiovascular disease (CVD) plays a salient role in human health that leads to severe problems even death. It is described that the range of disorders affecting the heart. Over 23 million people would be died from CVD every year by 2030. The cardiovascular disease may be preventable if they are properly predicted and proper kind of treatment should be provided at the initial stage so that 90% of them would be avoided. The extraction of information present inside the retinal tissues is the main function, which is used in the case of prediction of CVD and a suitable treatment should be given at the earlier stage of the diseases such as stroke, blood pressure, hyper tension, glaucoma etc. The retinal images is taken and then pre-processed. Then, they are segmented and featured extracted. By having their result, arteries and veins are classified through the support vector machine (SVM). The cup-to-disc ratio (CDR) is calculated by having the values of optical disc and optical cup diameters and the calculations are made to find the normal and abnormal images. Hence, the presence of CVD through the retinal images is predicted and analyzed in this paper.

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Keywords

Artery/vein classification, Boundary extraction, Feature extraction, Image edge detection, Medical diagnostic imaging, Retinal vessels, Thresholding (Imaging).

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