Strain imaging with a deformable mesh

Ultrasonic strain imaging has drawn much attention recently because of its ability to noninvasively provide information on spatial variation of the el astic properties of soft tissues. Traditionally, local strain is estimated by scaling and cross correlating pre- and postcompression ultrasound echo f ields. However, when the motion field generated by compression is more comp lex, scaling and cross correlation can no longer provide precise displaceme nt estimates because of signal decorrelation. We introduce a new algorithm based on the deformable mesh method. This algorithm can accommodate more ge neral forms of motion, namely, the motion that can be described by bilinear transformations. We ap. plied the new algorithm to three sets of data in o rder to evaluate its performance. In the first set of data, primitive motio ns such as shearing and rotation are simulated. The second set of data is c ollected by compressing a tissue-mimicking phantom with three hard inclusio ns. The third experiment involves an ex vivo pig kidney embedded in a block of gelatin. The results from all three experiments show improvements with the new algorithm over other methods.