基于压缩感知的 HIFU 回波信号降噪研究

由于传统的降噪处理方法很难干净地去除高强度聚焦超声(HIFU)信号中的噪声,提出利用压缩感知(CS)对 HIFU 回 波信号进行降噪。 在观测矩阵的设计中将传统的高斯随机观测矩阵改进为稀疏循环结构化矩阵,减少了构造观测矩阵和重构 信号的时间。 仿真实验表明,与带通滤波器、小波降噪方法和经验模态分解(EMD)降噪方法相比,该方法得到的信号的重构信 噪比(RSNR)更高,重构均方差(RMSE)和最大误差(ME)更小。 用不同方法对不同温度下获得的 HIFU 回波信号进行去噪并提 取二次谐波激发效率,发现采用该方法得到的二次谐波激发效率曲线方差和波动更小,验证了该降噪方法在实测信号中的优 越性。

Research on HIFU echo signal denoising based on compressed sensing technology

Since the traditional denoise method is difficult to fully remove the noise in the high intensity focused ultrasound ( HIFU) signal, it is proposed to use compressed sensing (CS) to denoise of HIFU echo signals. In the design of the observation matrix, the traditional Gaussian random observation matrix is improved to a sparse circular structured matrix, reduced time to construct observation matrix and reconstruct signal. Simulation experiments show that compared with the band-pass filter, wavelet denoise method and empirical mode decomposition (EMD) denoise method, the proposed method has higher reconstruction signal-to-noise ratio (RSNR), both reconstruction mean square error (RMSE) and maximum error (ME) are smaller. Using different methods to denoise HIFU echo signals obtained at different temperatures and extract the second harmonic excitation efficiency, it is found that the variance and fluctuation of the second harmonic excitation efficiency curve obtained by this method are smaller, which validate the denoise method superiority in actual signal.