Automated Segmentation of Cardiac Stenosis and MathematicalModeling of Myocardial Blood Flow for Early Detection of HeartAttack Using Advanced Imaging Techniques

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 6

Abstract

 Abstract: Heart attack is a leading cause of human deaths worldwide which occurs due to occlusion ofcoronary arteries and reduced blood flow. Hence, it requires early detection of disease in a non-invasive waythrough Cardiac Computed Tomography Angiogram images (CCTA). Local thresholding with Hessian matrixbased Frangi’s Vesselness filter has been applied for segmentation of coronary arterial branches. Stenosis asRegion of Interest can be quantified in cardiac arteries by using Sobel Gradient Edge operator with thresholdvalues 76 to 80. Mathematical model has been designed to measure the rate of change of blood flow in coronaryarteries by adopting hemodynamic fluid mechanics using Hagen Poiseuille’s law with Wall Shear Stressmethod. Computerized simulation results assist to detect healthy and cardiac diseased artery for betterdiagnosis

Authors and Affiliations

Supriya Agrawal

Keywords

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  • EP ID EP126984
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How To Cite

Supriya Agrawal (2014).  Automated Segmentation of Cardiac Stenosis and MathematicalModeling of Myocardial Blood Flow for Early Detection of HeartAttack Using Advanced Imaging Techniques. IOSR Journals (IOSR Journal of Computer Engineering), 16(6), 41-47. https://europub.co.uk/articles/-A-126984