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基于奇异值分解的多普勒超声信号杂波成分减少:一项模拟研究

Reduction of the clutter component in Doppler ultrasound signals based on singular value decomposition: a simulation study.

作者信息

Ledoux L A, Brands P J, Hoeks A P

机构信息

Department of Biophysics, Cardiovascular Research Institute Maastricht, Maastricht University, The Netherlands.

出版信息

Ultrason Imaging. 1997 Jan;19(1):1-18. doi: 10.1177/016173469701900101.

Abstract

In pulsed Doppler ultrasound systems, the ultrasound radiofrequency (RF) signals received can be employed to estimate noninvasively the time-dependent blood velocity distribution within and artery. The RF signals are composed of signals originating from clutter (e.g., vessel walls) and scatterers (e.g., red blood cells). The clutter, which is induced by stationary or slowly-moving structure interfaces, must be suppressed to get reliable estimates of the mean blood flow velocities. In conventional pulsed Doppler systems, this is achieved with a static temporal high-pass filter. The static cut-off frequency and the roll-off of these filters cause the culture not always to be optimally suppressed. This paper introduces a clutter removal filter that is based on Singular Value Decomposition (SVD). Unlike conventional high-pass filters, which take into account only the information of the temporal direction, the SVD filter makes use of the information of the temporal and spatial directions. The advantage of this approach is that it does not matter where the clutter is located in the RF signal. The performance of the SVD filter is examined with computer-generated Doppler RF signals. The results are compared with those of standard linear regression (SLR) filter. The performance of the SVD filter is good, especially if a large temporal window (i.e., approximately 100 RF signals) is applied, which improves the performance for low blood flow velocities, A major disadvantage of the SVD filter is its computational complexity, which increases considerably for larger temporal windows.

摘要

在脉冲多普勒超声系统中,接收到的超声射频(RF)信号可用于无创估计动脉内随时间变化的血流速度分布。RF信号由源自杂波(如血管壁)和散射体(如红细胞)的信号组成。由静止或缓慢移动的结构界面引起的杂波必须被抑制,以获得可靠的平均血流速度估计值。在传统的脉冲多普勒系统中,这是通过静态时间高通滤波器实现的。这些滤波器的静态截止频率和滚降特性导致杂波并不总是能得到最佳抑制。本文介绍了一种基于奇异值分解(SVD)的杂波去除滤波器。与仅考虑时间方向信息的传统高通滤波器不同,SVD滤波器利用了时间和空间方向的信息。这种方法的优点是,杂波在RF信号中的位置无关紧要。使用计算机生成的多普勒RF信号对SVD滤波器的性能进行了检验。将结果与标准线性回归(SLR)滤波器的结果进行了比较。SVD滤波器的性能良好,特别是在应用较大的时间窗口(即大约100个RF信号)时,这提高了对低血流速度的性能。SVD滤波器的一个主要缺点是其计算复杂度,对于较大的时间窗口,计算复杂度会显著增加。

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