Extraction of mean frequency information from Doppler blood flow signals using a matching pursuit algorithm
Extraction of mean frequency information from Doppler blood flow signals using a matching pursuit algorithm
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使用匹配追踪算法从多普勒血流信号中提取平均频率信息
DOI：
10.1016/j.sigpro.2008.05.019
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发表时间：
2008-11
影响因子：
4.4
通讯作者：
Bai, Baodan
中科院分区：
文献类型：
--
作者：
Shi, Xinling;Zhang, Yufeng;Ma, Huahong;Chen, Jianhua;Bai, Baodan
多普勒血流信号的强度加权平均频率（IWMF）波形与瞬时平均血流速度相关联，并且已经被发现对于测量体积流量和检测动脉狭窄非常有用。由于多普勒信号的非平稳性，这些涉及多普勒信号的应用需要在信号的短持续时间内精确估计IWMF。传统的短时傅立叶变换（STFT）方法要求信号在有限窗口内具有平稳性，这使得分析带宽相对较宽且随时间快速变化的信号时不准确。为了准确地估计多普勒IWMF波形，即使当时间流速是快速的（高非平稳性），我们提取的多普勒IWMF波形的时频分布估计使用匹配追踪（MP）与随机时频字典在本研究中。由于MP算法对瞬态结构的局部自适应性，它提供了一个非常紧凑的时频描述和信号的高时频分辨率。经典的（STFT为基础的）和MP为基础的算法之间的比较评估。实验结果表明，基于随机字典的最大匹配算法比基于短时傅里叶变换的算法估计的多普勒IWMF波形更准确。
The intensity-weighted mean frequency (IWMF) waveform of Doppler blood flow signals associates with the instantaneous mean blood velocities and has been found to be very useful to measure volumetric flow and detect arterial stenosis. These applications involving Doppler signals require the accurate estimation of the IWMF over short durations of the signal due to its nonstationarity. The traditional short-time Fourier transform (STFT) method requires stationarity of the signal during a finite window, making it inaccurate to analyze signals having relatively wide bandwidths that change rapidly with time. In order to accurately estimate the Doppler IWMF waveform, even when the temporal flow velocity is rapid (high nonstationarity), we extract the Doppler IWMF waveform from the time–frequency distribution estimated using the matching pursuit (MP) with stochastic time–frequency dictionaries in the present study. Because of its local adaptivity to transient structures, the MP algorithm provides a remarkably compact time–frequency description and high time–frequency resolution of a signal. A comparative evaluation has been made between the classic (STFT-based) and the MP-based algorithms. Experimental results indicate that the Doppler IWMF waveform estimated using the MP with stochastic dictionaries is more accurate than that based on the STFT.
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DOI：
10.1109/78.539028
发表时间：
1996-10
期刊：
IEEE Trans. Signal Process.
影响因子：
--
作者：
C. Taswell
通讯作者：
C. Taswell
影响因子：
2.9
作者：
P. Kalman;K. Johnston;P. Zuech;M. Kassam;K. Poots
通讯作者：
P. Kalman;K. Johnston;P. Zuech;M. Kassam;K. Poots
DOI：
10.1109/tasl.2006.889744
发表时间：
2007-03
期刊：
IEEE Transactions on Audio, Speech, and Language Processing
影响因子：
--
作者：
F. Gianfelici;G. Biagetti;P. Crippa;C. Turchetti
通讯作者：
F. Gianfelici;G. Biagetti;P. Crippa;C. Turchetti
影响因子：
4.6
作者：
Zhenyu Guo;L. Durand;H. C. Lee
通讯作者：
Zhenyu Guo;L. Durand;H. C. Lee
影响因子：
2.9
作者：
FISH, PJ
通讯作者：
FISH, PJ