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Rapid tracking of small displacements with ultrasound

机译：用超声波快速跟踪小位移

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Time-delay estimators, such as normalized cross correlation and phase-shift estimation, form the computational basis for elastography, blood flow measurements, and acoustic radiation force impulse (ARFI) imaging. This paper examines the performance of these algorithms for small displacements (less than half the ultrasound pulse wavelength). The effects of noise, bandwidth, stationary echoes, kernel size, downsampling, interpolation, and quadrature demodulation on the accuracy of the time delay estimates are measured in terms of bias and jitter. Particular attention is given to the accuracy and resolution of the displacement measurements and to the computational efficiency of the algorithms. In most cases, Loupas' two-dimensional (2-D) autocorrelator performs as well as the gold standard, normalized cross correlation. However, Loupas' algorithm's calculation time is significantly faster, and it is particularly suited to operate on the signal data format most commonly used in ultrasound scanners. These results are used to implement a real-time ARFI imaging system using a commercial ultrasound scanner and a computer cluster. Images processed with the algorithms are examined in an ex vivo liver ablation study.
机译：时延估计器（例如归一化互相关和相移估计）构成了弹性成像，血流测量和声辐射力脉冲（ARFI）成像的计算基础。本文研究了这些算法在小位移（小于超声脉冲波长的一半）下的性能。噪声，带宽，平稳回波，内核大小，下采样，内插和正交解调对时延估计精度的影响是根据偏差和抖动来衡量的。特别注意位移测量的精度和分辨率以及算法的计算效率。在大多数情况下，Loupas的二维（2-D）自相关器的性能与黄金标准归一化互相关一样好。但是，Loupas算法的计算时间明显更快，并且特别适合处理超声扫描仪中最常用的信号数据格式。这些结果用于使用商用超声扫描仪和计算机集群来实施实时ARFI成像系统。在离体肝脏消融研究中检查了用算法处理的图像。

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