Simultaneous Estimation of Left Ventricular Motion and Material Properties with Maximum a Posteriori Strategy

In addition to its technical merits as a challenging non-rigid motion and structural integrity analysis problem, quantitative estimation of cardiac regional functions and material characteristics has significant physiological and clinical values. We have earlier developed a stochastic finite element framework for the simultaneous estimation of myocardial motion and material parameters from medical image sequences with an extended Kalman filter approach. In this paper, we present a new computational strategy for the framework based upon the maximum a posteriori estimation principles, realized through the extended Kalman smoother, that produce a sequence of kinematics state and material parameter estimates from the entire sequence of observations. The system dynamics equations of the heart is constructed using a biomechanical model with stochastic parameters, and the tissue material and deformation parameters are jointly estimated from the periodic imaging data. Experiments with canine magnetic resonance images have been conducted with very promising results, as validated through comparison to the histological staining of post mortem myocardium.