Clutter filter design for ultrasound color flow imaging
Clutter filter design for ultrasound color flow imaging
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DOI：
10.1109/58.985705
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发表时间：
2002-02-01
影响因子：
3.6
通讯作者：
Kirstoffersen, K
中科院分区：
文献类型：
--
作者：
Bjærum, S;Torp, H;Kirstoffersen, K
为了获得高质量的彩色超声血流图像，必须充分抑制来自静止和缓慢运动组织的杂波信号。如果没有足够的杂波抑制，低速血流不能被测量，并且较高速度的估计将具有大的偏差。可用的少量样本（8至16）使得彩色血流成像中的杂波滤波成为一个具有挑战性的问题。在本文中，我们回顾和分析三类滤波器：有限脉冲响应（FIR），无限脉冲响应（IIR），和回归滤波器。根据频率响应以及使用自相关技术的平均血流速度估计器的偏差和方差评估滤波器的质量。对于FIR滤波器，通过允许非线性相位响应来改善频率响应。通过从分别在前向和后向方向上滤波的两个向量估计平均血流速度，最小相位滤波器的标准差显著低于线性相位滤波器。对于应用于短信号的IIR滤波器，输出信号的瞬态部分是重要的。我们分析了零，步骤和投影初始化，并发现投影初始化给出了最好的过滤器。对于回归滤波器，多项式基函数提供有效的杂波抑制。来自三个类别中的每一个的最佳滤波器给出了平均血流速度估计的可比偏倚和方差。然而，多项式回归滤波器和投影初始化IIR滤波器的频率响应比FIR滤波器稍好。
For ultrasound color flow images with high quality, it is important to suppress the clutter signals originating from stationary and slowly moving tissue sufficiently. Without sufficient clutter rejection, low velocity blood flow cannot be measured, and estimates of higher velocities will have a large bias. The small number of samples available (8 to 16) makes clutter filtering in color flow imaging a challenging problem. In this paper, we review and analyze three classes of filters: finite impulse response (FIR), infinite impulse response (IIR), and regression filters. The quality of the filters was assessed based on the frequency response, as well as on the bias and variance of a mean blood velocity estimator using an autocorrelation technique. For FIR filters, the frequency response was improved by allowing a non-linear phase response. By estimating the mean blood flow velocity from two vectors filtered in the forward and backward direction, respectively, the standard deviation was significantly lower with a minimum phase filter than with a linear phase filter. For IIR filters applied to short signals, the transient part of the output signal is important. We analyzed zero, step, and projection initialization, and found that projection initialization gave the best filters. For regression filters, polynomial basis functions provide effective clutter suppression. The best filters from each of the three classes gave comparable bias and variance of the mean blood velocity estimates. However, polynomial regression filters and projection-initialized IIR filters had a slightly better frequency response than could be obtained with FIR filters.