Performance of two dimensional displacement and strain estimation techniques using a phased array transducer.

The goal of this study was to investigate the applicability of conventional 2-D displacement and strain imaging techniques to phased array radiofrequency (RF) data. Furthermore, the possible advantages of aligning and stretching techniques for the reduction of decorrelation artefacts was examined. Data from both realistic simulations and phantoms were used in this study. Recently, the used processing concepts were successfully applied to linear array data. However, their applicability to sector scan data is not trivial because of the polar grid. Homogeneous and inhomogeneous tissue phantoms were simulated at a range of strains (0 to 5%) using Field II((c)). The inhomogeneous phantom, a commonly used tumor/lesion model, was also constructed using gelatin/agar solutions. A coarse-to-fine displacement algorithm was applied, using aligning and stretching to enhance re-correlation. Vertical and horizontal strains were reconstructed from the axial and lateral displacements. Results revealed that the error on displacement estimates was lower when using 2-D data windows rather than 1-D windows. For regions at large depths and large insonification angles, the allowed lateral window size was limited. Still, 1-D windows resulted in larger errors. The re-correlation techniques resulted in a significant increase in the elastographic signal-to-noise ratio (SNRe) and elastographic contrast-to-noise ratio (CNRe) of the vertical and horizontal strain components. An increase of the SNRe of 5-20 dB was observed over a range of strains (0.5 to 5.0%). In the inhomogeneous phantom, a vertical SNRe of 27.7 dB and a horizontal SNRe of 16.7 dB were measured in the background. The vertical and horizontal CNRe were 35 dB and 23.1 dB, respectively. For the experimental data, lower SNRe (vertical: 19.1 dB; horizontal: 11.4 dB) and CNRe (vertical: 33.3 dB; horizontal: 12.5 dB) were found. In conclusion, 2-D window matching of sector scan data is feasible and outperforms 1-D window matching. Furthermore, the use of re-correlation techniques enhances both precision and contrast of strain images.