Myocardial Ischemia is a main malady in causing demises overall which pieces of information to heart assault. This condition happens when there is a starvation of oxygenated blood supply to the heart which makes the dead cells. Hereafter it requires convenient determination of infections utilizing the genuine pictures of Cardiac Computed Tomography Angiogram pictures. Preprocessing is finished with middle channel and Canny edge identifier took after by Hessian based FrangiVesselness channel by applying kept thresholding that identifies bend structures. Secondly, for similar pictures by the proposed method utilizing Sobel channel and K_ implies Clustering and using morphological procedures like disintegration and expansion for division of branches of coronary supply routes and the highpoints resembling length, width, territory, border, weight of blood stream and rate Stenosis are confirmed with nearby reproduction. The proposed numerical model clarifies rate of progress of blood in coronary supply routes utilizing Euclidean separation. Thirdly, experts also make a diagnosis of the identical images and conclude the ground truth values. The outcomes for computing the percentage of Stenosis demonstrates that the projected second strategy affirms the more exact acknowledgment with the approved ground truth outcomes with less computational time and in height accurateness. Factual Parameters alike Mean, Standard deviation, Skew, Energy and Entropy esteems are additionally numerated that shows Sobel filter with K_ Means Clustering modus operandi merits best. Additionally the arrangements of the levels of heart assault as Normal, Introductory, Minor and Critical utilizing k-NN (k-Nearest Neighbor) classifier are accumulated and our projected scheme originate faithfully equivalent to the ground realitytaxonomy. © 2018, Institute of Advanced Scientific Research, Inc. All rights reserved.