Two-dimensional (2D) cross-correlation algorithms are necessary to estimate local displacement vector information for strain imaging. However, most of the current two-dimensional cross-correlation algorithms were developed for linear array transducers. Although sector and phased array transducers are routinely used for clinical imaging of abdominal and cardiac applications, strain imaging for these applications has been performed using one-dimensional (1D) cross-correlation analysis. However, one-dimensional cross-correlation algorithms are unable to provide accurate and precise strain estimation along all the angular insonification directions which can range from −45° to 45° with sector and phased array transducers. In addition, since sector and phased array based images have larger separations between beam lines as the pulse propagates deeper into tissue, signal decorrelation artifacts with deformation or tissue motion are more pronounced. In this article, the authors propose a multilevel two-dimensional hybrid algorithm for ultrasound sector and phased array data that demonstrate improved tracking and estimation performance when compared to the traditional 1D cross-correlation or 2D cross-correlation based methods. Experimental results demonstrate that the signal-to-noise and contrast-to-noise ratio estimates improve significantly for smaller window lengths for the hybrid method when compared to the currently used one-dimensional or two-dimensional cross-correlation algorithms. Strain imaging results on ex vivo thermal lesions created in liver tissue and in vivo on cardiac short-axis views demonstrate the improved image quality obtained with this method.
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