超声血流成像中基于动态域的回归和奇异值分解的杂波抑制方法

Clutter suppression method based on dynamic region regression and singular value decomposition in ultrasound flow image

针对超声彩色血流成像(CFI)中杂波引起血流速度估计不准确的问题,提出了一种基于动态域的多项式回归和奇异值分解(SVD)的杂波抑制方法——ARS算法。首先,根据回波信号的时域特性和能量强度,采用动态划分法区分出信号所属范围;其次,按照信号的所属范围选取多项式回归法或SVD法动态地去除杂波成分。将所提算法与投影初始化无限脉冲响应(IIR)法、非平稳滤波法、回归滤波法和SVD法等杂波抑制方法进行仿真对比,实验结果表明:所提算法能够较好地抑制组织运动干扰(组织区信号的运动速度几乎为零,且滤波后的杂波血流比约为5.427 d B),估计出的最大血流速度(0.968 m/s)最接近于理论值,血流分布均匀,并能较好地保持血流速度剖面的完整性,得到的血流速度图像真实,质量较高。

For the inaccurate problem of the estimation of the blood flow velocity which is caused by the clutter signal in ultrasound Color Flow Imaging（ CFI）, this paper proposed a clutter suppression method based on dynamic region polynomial regression and Singular Value Decomposition（ SVD）, called ARS algorithm. First, according to the time-domain characteristics and the energy intensity of the echo signal, this method adopted the dynamic partitioning method to distinguish the range of signal; then, according to the divided range, polynomial regression method or SVD method was selected to dynamically reject the clutter signal. This paper made a simulation to compare the proposed method with the projection initialized Infinite Impulse Response（ IIR） filter, the non-stationary filter, the regression filter and the SVD algorithm. The experimental results show that the proposed method can completely reject the interference of tissue motion（ the velocity is almost zero in the tissue area and the clutter-to-blood ratio is about 5. 427 d B after the clutter suppressing is implemented）, the estimated maximum blood flow velocity（ 0. 968 m / s） is close to the theoretical value and the blood flow distributes uniformly,the integrity of the blood flow velocity profile can be better maintained and the achieved blood flow velocity map illustrates the authentic flow velocity and high image quality.