LAUSR

Abstract In the versatile advanced world, diseases due to the cardiovascular disease (CVD) play a major role in human health disorders event leads to death. CVD deaths accounts for 80% in males and 75% in females. Cardiovascular diseases are the leading cause of death globally. By 2030, over 23 million people will die from CVD every year. Up to 90% of cardiovascular disease may be preventable if they are properly recognized and correct treatment should be given at the earlier stage. This paper undergoes one of the key factors to find CVD is through retinal vessels, the processes involved in those measurements could predict the presence of diseases. The main function that is involved in the retinal vessels is the extraction of information present inside the tissues which is used in the case of recognition and treatment towards cardiovascular diseases such as stroke, blood pressure, hyper tension, glaucoma etc. The retinal image taken is filtered and then segmented. Their result is used for arteries and vein classification through the support vector machine (SVM). By detecting the optic cup and optic disc measurement, cup-to-disc ratio (CDR) is calculated here. By using artificial neural networks (ANN), the presence of CVD is recognized and their parameters are measured. Hence, the presence of CVD is recognized through the retinal images are detected in this paper.