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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >An adaptive displacement estimation algorithm for improved reconstruction of thermal strain
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An adaptive displacement estimation algorithm for improved reconstruction of thermal strain

机译：一种改进的热应变重构的自适应位移估计算法

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摘要

Thermal strain imaging (TSI) can be used to differentiate between lipid and water-based tissues in atherosclerotic arteries. However, detecting small lipid pools in vivo requires accurate and robust displacement estimation over a wide range of displacement magnitudes. Phase-shift estimators such as Loupas' estimator and time-shift estimators such as normalized cross-correlation (NXcorr) are commonly used to track tissue displacements. However, Loupas' estimator is limited by phase-wrapping and NXcorr performs poorly when the SNR is low. In this paper, we present an adaptive displacement estimation algorithm that combines both Loupas' estimator and NXcorr. We evaluated this algorithm using computer simulations and an ex vivo human tissue sample. Using 1-D simulation studies, we showed that when the displacement magnitude induced by thermal strain was >λ/8 and the electronic system SNR was >25.5 dB, the NXcorr displacement estimate was less biased than the estimate found using Loupas??? estimator. On the other hand, when the displacement magnitude was ???λ/4 and the electronic system SNR was ???25.5 dB, Loupas' estimator had less variance than NXcorr. We used these findings to design an adaptive displacement estimation algorithm. Computer simulations of TSI showed that the adaptive displacement estimator was less biased than either Loupas' estimator or NXcorr. Strain reconstructed from the adaptive displacement estimates improved the strain SNR by 43.7 to 350% and the spatial accuracy by 1.2 to 23.0% (P
机译：热应变成像（TSI）可用于区分动脉粥样硬化动脉中的脂质和水基组织。但是，在体内检测小的脂质池需要在宽范围的位移范围内进行准确而可靠的位移估计。相移估计器（例如Loupas估计器）和时移估计器（例如归一化互相关（NXcorr））通常用于跟踪组织位移。但是，Loupas的估计器受相位包装的限制，而当SNR低时，NXcorr的性能会很差。在本文中，我们提出了一种自适应的位移估计算法，该算法结合了Loupas的估计器和NXcorr。我们使用计算机模拟和离体人体组织样本评估了该算法。使用一维模拟研究，我们发现，当由热应变引起的位移幅度>λ/ 8且电子系统SNR> 25.5 dB时，NXcorr位移估算的偏差要小于使用Loupas估算的偏差。估算器。另一方面，当位移量为λ/ 4且电子系统SNR为25.5dB时，Loupas估计器的方差小于NXcorr。我们使用这些发现来设计自适应位移估计算法。 TSI的计算机仿真表明，自适应位移估算器的偏差要比Loupas估算器或NXcorr少。根据自适应位移估算值重建的应变将应变SNR提高了43.7至350％，将空间精度提高了1.2至23.0％（P

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