Retinal Vessels Segmentation Using Supervised Classifiers for Identification of Cardio Vascular Diseases

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The risk of cardio vascular diseases can be identified by measuring the retinal blood vessel. The identification of wrong blood vessel may result in wrong clinical diagnosis. This proposed system addresses the problem of identifying the true vessel by vascular structure segmentation. In this proposed model the segmented vascular structure is modelled as a vessel segment graph and the true vessels are identified by using supervised classifier approach. This paper proposes a post processing step in diagnose cardiovascular diseases which can be identified by tracking a true vessel from the optimal forest in the graph given a set on constraints.