【摘要】 目的:探求一种基于Hilbert-Huang变换的医学超声信号去噪方法。方法:提出了一种基于Hilbert-Huang变换的医学超声信号去噪方法。首先对含噪超声信号进行经验模式分解,得到各阶IMF分量,然后对高频的IMF分量用阈值方法进行处理,把经过阈值处理的高频的IMF分量和低频IMF分量进行叠加,得到重构的去噪信号。结果:仿真实验表明,基于Hilbert-Huang变换的医学超声信号去噪方法可以有效地降噪。结论:Hilbert-Huang变换的医学超声信号去噪方法在自适应性和先验性方面优于基于小波的去噪方法。更多还原

【Abstract】 Objective: A denoising method of medical ultrasonic signal based on Hilbert-Huang Transform is explored.Methods: A denoising method of medical ultrasonic signal based on Hilbert-Huang Transform was presented.Firstly,medical ultrasonic signal polluted by noise is decomposed into several Intrinsic Mode Function(IMF) by empirical mode decomposition.Secondly,the intrinsic mode functions of high frequency are processed using threshold method,and we add these IMFs with IMFs of low frequency to achieve denoising signal.Results: Simulation experiments show that the HHT method is efficient to denoising noises.Conclusions: The denoising method based on HHT has achieved better adaptive ability and less former information than wavelet transform method.更多还原