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. © 2011 Springer-Verlag.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6891 LNCS, pp. 420–427). https://doi.org/10.1007/978-3-642-23623-5_53
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