Abstract
Cardiac deformation recovery is to recover quantitative subject-specific myocardial deformation from imaging data. In the last decade, cardiac physiological models derived from anatomy, biomechanics, and cardiac electrophysiology have become increasingly popular in constraining the recovery problems because of their physiological meaningfulness. Although physiological models with various electrical and biomechanical components have been adopted by different frameworks and have exhibited promising results, these models have not been systematically compared under the same recovery framework, input data, and experimental setups. As different models comprise varying physiological plausibilities and complexities, comparisons under the same settings can aid choosing the proper models for specific goals and available resources. In this paper, under a state-space filtering framework for statistically optimal couplings between models and image data, we compare the performances of six different cardiac physiological models with different biomechanical constraints. Experiments were performed on synthetic data for quantitative comparisons, and on clinical data for their capabilities in identifying pathological situations.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Shi, P., Liu, H.: Stochastic finite element framework for simultaneous estimation of cardiac kinematic functions and material parameters. Medical Image Analysis 7, 445–464 (2003)
Sermesant, M., Delingette, H., Ayache, N.: An electromechanical model of the heart for image analysis and simulation. IEEE Transactions on Medical Imaging 25(5), 612–625 (2006)
Wong, K.C.L., Wang, L., Zhang, H., Shi, P.: Nonlinear cardiac deformation recovery from medical images. In: IEEE International Conference on Image Processing, pp. 2513–2516 (2009)
Glass, L., Hunter, P., McCulloch, A. (eds.): Theory of Heart: Biomechanics, Biophysics, and Nonlinear Dynamics of Cardiac Function. Springer, Heidelberg (1991)
Usyk, T.P., Mazhari, R., McCulloch, A.D.: Effect of laminar orthotropic myofiber architecture on regional stress and strain in the canine left ventricle. Journal of Elasticity 61, 143–164 (2000)
Aliev, R.R., Panfilov, A.V.: A simple two-variable model of cardiac excitation. Chaos, Solitons & Fractals 7(3), 293–301 (1996)
Julier, S.J., Uhlmann, J.K.: Unscented filtering and nonlinear estimation. Proceedings of the IEEE 92(3), 401–422 (2004)
Nash, M.: Mechanics and Material Properties of the Heart using an Anatomically Accurate Mathematical Model. PhD thesis, The University of Auckland (1998)
Tim Marcus, J., Götte, M.J.W., van Rossum, A.C., Kuijer, J.P.A., Heethaar, R.M., Axel, L., Visser, C.A.: Myocardial function in infarcted and remote regions early after infarction in man: assessment by magnetic resonance tagging and strain analysis. Magnetic Resonance in Medicine 38(5), 803–810 (1997)
PhysioNet/Computers in Cardiology challenge: electrocardiographic imaging of myocardial infarction (2007), http://www.physionet.org/challenge/2007/
Perperidis, D., Mohiaddin, R.H., Rueckert, D.: Spatio-temporal free-form registration of cardiac MR image sequences. Medical Image Analysis 9(5), 441–456 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wong, K.C.L., Wang, L., Liu, H., Shi, P. (2011). A Comparative Study of Physiological Models on Cardiac Deformation Recovery: Effects of Biomechanical Constraints. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6891. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23623-5_53
Download citation
DOI: https://doi.org/10.1007/978-3-642-23623-5_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23622-8
Online ISBN: 978-3-642-23623-5
eBook Packages: Computer ScienceComputer Science (R0)