Estimating cardiac motion from image sequences using recursive comb filtering

A framework for temporal analysis of left ventricular (LV) endocardial wall motion is presented. This approach uses harmonic estimation to model the periodic nature of cardiac motion. A method for flow vector computation is presented which defines a relationship between image-derived, shape-based correspondences and a more desirable, smoothly varying, set of correspondences. A recursive filter is then constructed which takes into consideration this relationship as well as knowledge of temporal trends. The trajectories of magnetic resonance (MR) contrast markers implanted in the LV wall are compared with trajectories estimated by the filter. The results of this comparison confirm that although cardiac motion is a 3-D problem, 2-D analysis provides a rich testing ground for algorithm development.