Key result
A new peak-searching algorithm for ultrasonic elastography sped up the implementation process by approximately 79% compared with the standard cross-correlation method and improved signal-to-noise ratio.
A novel peak-searching algorithm for ultrasonic elastography significantly improves processing speed and image quality metrics compared to standard methods.
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May accelerate elastography processing in research; leaves open clinical validation before practice change.
Tissue axial strain estimation with ultrasound elastography has become a hot field in recent years. However, for keypoints tracking-based elastography algorithms, locating extrema in multimodal ultrasonic radiofrequency signals is still a challenging problem. In this paper, a new method is proposed to locate the local maxima and minima of the RF signals directly without derivation operation. This algorithm can accurately locate extrema even if disturbed peaks resulting from different noise exist. Furthermore, the new algorithm can speed up approximately 79% of the implementation process as compared with the standard cross-correlation method on the same computing platform. In addition, the elastographic signal-to-noise ratio and the contrast-to-noise ratio are also significantly improved with this new method.
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Chen et al. (2017) studied this question. Fast peak-searching algorithm vs. Standard cross-correlation method was evaluated on Implementation process speed, elastographic signal-to-noise ratio, and contrast-to-noise ratio. A new peak-searching algorithm for ultrasonic elastography sped up the implementation process by approximately 79% compared with the standard cross-correlation method and improved signal-to-noise ratio.
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