Implementing Archimedean Spiral Approach to Evaluate Left Ventricular Myocardial Functions
Keywords:image processing, Biomedical Engineering,
Heart disease can be determined by the calculating regional and global wall motion of the left ventricular (LV). In this research, we designed a dynamic simulation tool using Computed Tomography (CT) images that helps to find the difference between actual and simulated left ventricular functions. In this study, thirteen healthy subjects were involved with actual and simulated left ventricular functions. We obtained the high correlation between actual left ventricular wall motion (ALVWM) and simulated left ventricular wall motion (SLVWM) which is (r = 0.99). Our results validate that our simulation tool is feasible for simulating left ventricular motion.
(1) Kones, R. Primary prevention of coronary heart disease: integration of new data, evolving views, revised goals, and role of rosuvastatin in management. A comprehensive survey. Drug design, development and therapy, 2011.
(2) Cicala, Silvana, et al. "Prevalence and prognostic significance of wall-motion abnormalities in adults without clinically recognized cardiovascular disease: the Strong Heart Study." Circulation, 2007.
(3) Park, J., Metaxas, D., Young, A., & Axel, L. Model-based analysis of cardiac motion from tagged MRI data. In Computer-Based Medical Systems, 1994., Proceedings 1994 IEEE Seventh Symposium on (pp. 40-45). IEEE. 1994.
(4) Monga and N. Ayache. From voxel to curvature. IEEE Computer Vision and Pattern Recognition, 1991, 644-649.
(5) P. T. Sander and S. W. Zucker. Inferring surface trace and differential structure from 3D images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(9):833-854.
(6) J. Park, D. Metaxas, A. A. Young, and L. Axel, "Deformable models with parameter functions for cardiac motion analysis from tagged MRI data, “IEEE Transactions on Medical Imaging, 1996.
(7) J. Huang, D. Abendschein, V. G. Davila-Roman, and A. A. Amini, "Spatio-temporal tracking of myocardial deformations with a 4-D B-spline model from tagged MRI," IEEE Transactions on Medical Imaging, 1999.
(8) Adams R, Bischof L. Seeded Region Growing. IEEE Transactions on pattern analysis and machine intelligence 1994: 16:641-647.
(9) Walser, H.; Hilton, P.; Pedersen, J.; Mathematical Association of America. Symmetry. Mathematical Association of America. p. 27. ISBN 9780883855324. Retrieved 2014-10-06.
(10) Kass, M., Witkin, A., & Terzopoulos, D. Snakes: Active contour models. International journal of computer vision, 1(4), 1998.