Abstract
In this study, a new inverse analysis framework for estimation of myocardium constitutive parameters is established. In this framework, by using cardiac magnetic resonance image of realistic human left ventricular, a more realistic, finite element analysis model for analyzing the deformation of left ventricle during diastole is introduced. The anisotropic nonlinear Holzapfel-Ogden constitutive model is used to describe the material behavior of myocardium. Estimating the parameters as for the inverse problem of left ventricle deformation, a novel hybrid simplex and particle swarm optimization algorithm is proposed to estimate the parameters of myocardium’s constitutive model. Numerical examples presents that finite element analysis results and the estimated parameters are in good agreement with the experimental data reported in literature, comparing with current optimization algorithm, the presented hybrid optimal algorithm can estimate the constitutive parameters more efficient. The efficiency and validity of the proposed parameter estimation framework is demonstrated.
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