|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
A HYBRID DISPLACEMENT ESTIMATION METHOD FOR ULTRASONIC ELASTICITY IMAGING
L.Chen, R.J. Housden, G.M. Treece, A.H. Gee and R.W. Prager
Axial displacement estimation is fundamental to all freehand, quasistatic, ultrasonic strain imaging systems. In this paper, we present a novel estimation method that combines elements of multi-level correlation and phase-zero search to achieve the noise tolerance of the former and the speed of the latter. Given typical clinical B-scans, the hybrid method can generate more than 25 strain images per second on commodity hardware. The paper includes a full description of the hybrid method, in vivo examples to illustrate the method's clinical relevance, and finite element simulations to demonstrate its superior accuracy compared with previously published alternatives.
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