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A multi-scale algorithm for ultrasonic strain reconstruction under moderate compression

机译:中压缩下超声应变重建的多尺度算法

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摘要

Since the waveform of an echo is more distorted under larger compression, elastography can be applied in cases where the compression is only a few percent. To reduce errors due to distortion of the echo waveform, a novel algorithm (i.e. themultiscale correlation algorithm) for strain profile reconstruction is proposed in this article. The basic idea of this method is to simulate human vision: first, we locate the region of the target, and then match the detail within this region and make acomprehensive criterion. Based on this concept, three different approach algorithms are proposed and investigated: (1) the two-step method, (2) the multi-scale correlation algorithm, and (3) the extended multi-scale correlation algorithm. To evaluate thealgorithms proposed in this work, a computer simulation model is used and a sequence of simulation experiments are performed. The correlating specificity is used as a criterion for evaluating the performance characteristics of the correlation estimation.The results show that the extended multi-scale correlation algorithm performs significantly better than the other two methods proposed in this article under moderate compression ratios. The extended multi-scale correlation algorithm is applicable to bothsmall and moderate compression ratios. This novel algorithm may provide a useful tool for the clinical application of elastograms.
机译:由于回声的波形在较大压缩下会更加失真,因此可以在压缩率仅为百分之几的情况下应用弹性成像。为了减少由于回波波形失真引起的误差,本文提出了一种新的应变分布重构算法(即多尺度相关算法)。该方法的基本思想是模拟人类视觉:首先,确定目标区域,然后匹配该区域内的细节,并制定一个综合标准。基于这一概念,提出并研究了三种不同的算法:(1)两步法;(2)多尺度相关算法;(3)扩展多尺度相关算法。为了评估本文提出的算法,使用了计算机仿真模型并进行了一系列仿真实验。相关特异性被用作评估相关估计性能特征的标准。结果表明,在中等压缩比下,扩展的多尺度相关算法的性能明显优于本文提出的其他两种方法。扩展的多尺度相关算法适用于中小压缩比。这种新颖的算法可以为弹性成像的临床应用提供有用的工具。

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