A generalized speckle tracking algorithm for ultrasonic strain imaging using dynamic programming.

This study developed an improved motion estimation algorithm for ultrasonic strain imaging that employs a dynamic programming technique. In this article, we model the motion estimation task as an optimization problem. Since tissue motion under external mechanical stimuli often should be reasonably continuous, a set of cost functions combining correlation and various levels of motion continuity constraint were used to regularize the motion estimation. To solve the optimization problem with a reasonable computational load, a dynamic programming technique that does not require iterations was used to obtain displacement vectors in integer precision. Then, a subsample estimation algorithm was used to calculate local displacements in fractional precision. Two implementation schemes were investigated with in vivo ultrasound echo data sets. We found that the proposed algorithm provides more accurate displacement estimates than our previous algorithm for in vivo clinical data. In particular, the new algorithm is capable of tracking motion in more complex anatomy and increases strain image consistency in a sequence of images. Preliminary results also suggest that a significantly longer sequence of high contrast strain images could be obtained with the new algorithm compared with the previous algorithm. The new algorithm can also tolerate larger motion discontinuities (e.g., cavity in an anthropomorphic uterine phantom).