超声多普勒栓子信号的小波特征提取及分类应用  

The wavelet based feature extraction and classification of Doppler ultrasound embolic signals

作　　者：陈一骄[1] 汪源源[1] 王威琪[1] 周华琳[2] 傅建辉[2] 

机构地区：[1]复旦大学电子工程系,上海200433 [2]复旦大学附属华山医院,上海200040

出　　处：《声学学报》2007年第6期517-524,共8页Acta Acustica

基　　金：国家自然科学基金(30570488)

摘　　要：采用超声多普勒技术无损检测栓子,有积极的临床意义。为降低探头或病人移动引起的干扰对检测栓子的影响,从超声多普勒信号小波变换的两个角度研究相应特征参数的提取。先根据小波尺度图分析信号波形的奇异性,提取表征尺度图特征的横向和纵向参数;然后提出自适应小波包基分析方法,提取表征信号最优逼近特性的能量、尺度等参数。综合两方面特征,通过求解Fisher广义最佳鉴别平面,建立起一个超声多普勒栓子信号分类系统。通过对300例仿真和298例临床采集的脑动脉超声多普勒信号的试用。结果表明:系统对训练集和测试集的栓子信号检测率分别达99.0%和98.5%。可见,本方法比传统方法在检测准确性上有了较大的提高,有望应用于栓子信号的临床自动检测。The non-destructive detection of circulating emboli with Doppler ultrasound technique is of active significance in the clinical application. In order to eliminate the drawbacks of artifacts brought by the movement of probes or patients and detect emboli accurately, relevant feature parameters are extracted from two angles of the wavelet transform of Doppler signals. Firstly, to analyze the singularity of the signal waveform through its wavelet scalogram, transverse and longitudinal parameters are extracted to represent the scalogram characteristics. A novel method is then proposed based on the adaptive wavelet packet basis, from which several parameters such as energy, scale, etc. are extracted to represent the optimized signal approximation features. With all the feature parameters in the two aspects, a classification system is established for Doppler Ultrasound embolic signals by solving the generalized Fisher discriminant plane. From experiments on 300 cases simulated and 298 cases clinical Doppler ultrasound signals of cerebral arteries. it is shown that the proposed system can achieve the emboli detection rates of 99.0% and 98.5% for the training set and the testing set respectively. Therefore this method makes great improvement of emboli detection compared to traditional methods and has the possibility to be applied in the automatic detection of clinical emboli.

关 键 词：超声多普勒信号 特征提取 小波变换 分类系统 应用 无损检测 临床意义 最佳鉴别平面 

分 类 号：O426[理学—声学]