匹配追踪算法的超声多普勒血流信号降噪研究

Research for Ultrasonic Doppler Blood Signal De-noising Based on the Matching Pursuit Algorithm

超声多普勒在临床医学中具有广泛的应用,但由于超声多普勒血流信号中夹杂了大量的噪声严重影响了时频声谱图的清晰度,所以必须采用一定的措施消除噪声。本文分别利用离散小波变换算法、小波包变换算法和匹配追踪算法对超声多普勒血流信号进行分解、变换以及降噪处理,并通过仿真实验,给出了不同信噪比情况下,对基于三种算法处理后的信号时域波形和频域波形进行了比较,证实了匹配追踪算法是一种非常适合于对像超声多普勒血流信号这样的频率带宽随时间变化很快的强噪声背景的信号进行噪声处理的算法。

Doppler ultrasound has been used extensively in clinical applications,however,the determination of the maximum frequency is often inaccurate owing to extra frequency components.As a result,the indices based on the extracted maximum frequency cannot be considered as accurate to make diagnoses.Therefore,a de-noising algorithm is needed to objectively calculate the diagnoses parameters.This paper uses discrete wavelet transform algorithm,the wavelet packet transform algorithm and the matching pursuit algorithm to deal with ultrasonic doppler blood flow signal by decomposition,transform and noise reduction.The simulation results are given to show the performance of the improved algorithm and the original algorithm at the different SNR cases.Simulation results are presented to verify the efficacy of the proposed algorithm.