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Computational and Mathematical Methods in Medicine
Volume 2016 (2016), Article ID 2695962, 12 pages
Research Article

Patient-Specific Computational Models of Coronary Arteries Using Monoplane X-Ray Angiograms

1School of Medicine, University of California, San Diego, CA 92093, USA
2Department of Electrical Engineering, The Petroleum Institute, P.O. Box 2533, Abu Dhabi, UAE

Received 2 March 2016; Revised 20 May 2016; Accepted 26 May 2016

Academic Editor: Po-Hsiang Tsui

Copyright © 2016 Ali Zifan and Panos Liatsis. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Coronary artery disease (CAD) is the most common type of heart disease in western countries. Early detection and diagnosis of CAD is quintessential to preventing mortality and subsequent complications. We believe hemodynamic data derived from patient-specific computational models could facilitate more accurate prediction of the risk of atherosclerosis. We introduce a semiautomated method to build 3D patient-specific coronary vessel models from 2D monoplane angiogram images. The main contribution of the method is a robust segmentation approach using dynamic programming combined with iterative 3D reconstruction to build 3D mesh models of the coronary vessels. Results indicate the accuracy and robustness of the proposed pipeline. In conclusion, patient-specific modelling of coronary vessels is of vital importance for developing accurate computational flow models and studying the hemodynamic effects of the presence of plaques on the arterial walls, resulting in lumen stenoses, as well as variations in the angulations of the coronary arteries.