Quantification of left ventricular (LV) deformation from 3D image sequences (4D data) is important for the assessment of myocardial viability, which can have important clinical implications. To date, feature information from either Magnetic Resonance, computed tomographic or echocardiographic image data has been assembled with the help of different interpolative models to estimate LV deformation. These models typically are designed to be computationally efficient (e.g. regularizing strategies using B-splines) or more physically realistic (e.g. finite element approximations to biomechanical models), but rarely incorporate both notions. In this paper, we combine an approach to the extraction and matching of image-derived point features based on local shape properties with a boundary element model. This overall scheme is intended to be both computationally efficient and physically realistic. In order to illustrate this, we compute strains using our method on canine 4D MR image sequences and compare the results to those found from a B-spline-based method (termed extended free-form deformation (EFFD)) and a method based on finite elements (FEM). All results are compared to displacements found using implanted markers, taken to be agold standard.