A new shape-based tracking algorithm using bending energy and optimization functional provides a more accurate estimate of perceived left ventricular wall motion than previous techniques.
A new approach for tracking and quantifying the nonrigid, nonuniform motion of the left ventricular (LV) endocardial wall from cardiac image sequences, on a point-by-point basis over the entire cardiac cycle, is presented. The first step in the algorithm uses one of two approaches to estimate the LV boundary from each image in the sequence. Motion computation involves first matching local segments on one contour to segments on the next contour in the sequence using a shape-based strategy based on bending energy. Results from the match process are incorporated into an optimization functional, along with a smoothness term. The nearest local minimum of the functional to the initial match is found, resulting in a smooth flow field that is consistent with the match data. The computation is performed for all pairs of frames in the temporal sequence and equally sampled points on one contour are tracked throughout the sequence, resulting in a composite flow field over the entire sequence. The method provides a more accurate estimate of perceived motion than previous techniques. >
Duncan et al. (Wed,) conducted a other in Left ventricular wall motion tracking. Shape-based tracking algorithm vs. Previous techniques was evaluated on Accuracy of perceived motion estimate. A new shape-based tracking algorithm using bending energy and optimization functional provides a more accurate estimate of perceived left ventricular wall motion than previous techniques.