Ultrasonic strain imaging has drawn much attention recently because of its ability to noninvasively provide information on spatial variation of the elastic properties of soft tissues. Traditionally, local strain is estimated by scaling and cross correlating pre- and postcompression ultrasound echo fields. However, when the motion field generated by compression is more complex, scaling and cross correlation can no longer provide precise displacement estimates because of signal decorrelation. We introduce a new algorithm based on the deformable mesh method. This algorithm can accommodate more general forms of motion, namely, the motion that can be described by bilinear transformations. We applied the new algorithm to three sets of data in order to evaluate its performance. In the first set of data, primitive motions such as shearing and rotation are simulated. The second set of data is collected by compressing a tissue-mimicking phantom with three hard inclusions. 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.
- Motion detection
- Tissue strain
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Acoustics and Ultrasonics