基于小波包的血栓超声多普勒信号检测
Embolic Doppler ultrasound signal detection using the wavelet packet analysis
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摘要: 提出了基于小波包分解的血栓超声多普勒信号检测方法。利用小波包分解血栓多普勒信号,计算每一子带信号的时间散度,并从中提取与血栓敏感的特征参数进行分类。利用本方法对300例仿真多普勒信号和163例临床采集的大脑中动脉多普勒信号进行分析,得到的检测总误判率比用传统声谱分析方法降低约13%。表明:该方法有效克服了传统声谱分析法中短时傅里叶变换存在的时频分辨率矛盾,提高了血栓多普勒信号自动检测的准确性,可为临床检测血栓提供更为可靠的参数。Abstract: A Doppler ultrasound analysis method based on wavelet package transform was proposed for embolic detection. The embolic Doppler signal was firstly decomposed using the wavelet packet. Then the sensitive characteristics were calculated from each sub-band signal and used in the emboli classification. This method was applied to analyze 300 cases simulated and 163 cases clinical Doppler signals. The error ratio of embolic detection using this method was 13 percents lower than that using the traditional spectrogram analysis method. It was shown that this method overcame the limit between time and frequency resolution in the short time Fourier transform, improved the accuracy of embolic detection greatly and extracted more reliable parameters for the clinical diagnosis.