Sitemap  |  Contact  |  Home  |  中文  |  CAS  |  Director’s Email
International Cooperation
Education & Training
Societies & Publications
Chinese Journal of Acoustics
 
 
  Location:Home>Chinese Journal of Acoustics
Detecting Doppler ultrasound embolic signals using the wavelet-based feature extraction algorithm (2008 No.4)
Author:
ArticleSource:
Update time: 2008/11/05
Viewed:
Close
Text Size: A A A
Print

CHEN Yijiao1 WANG Yuanyuan1 WANG Weiqi1 ZHOU Hualin2 FU Jianhui2

 

(1 Department of Electronic Engineering, Fudan University  Shanghai 200433)

 

(2 Huashan Hospital Affiliated with Fudan University  Shanghai 200040)

 

Received Aug.8, 2007

 

Revised Mar.25, 2008 

 

Abstract The non-invasive detection of circulating emboli with the Doppler ultrasound technique is of active significance in clinical applications. In order to eliminate 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. The singularity of the signal waveform is analyzed based on its wavelet scalogram; then transverse and longitudinal parameters are extracted to represent the scalogram characteristics. A novel method is proposed based on the adaptive wavelet packet basis, from which several parameters such as the energy, the scale, etc. are extracted to represent the optimized signal approximation features. With all feature parameters in two aspects, a classification system is established for Doppler Ultrasound embolic signals by solving the generalized Fisher discriminant plane. From experiments on 300 simulated and 298 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 an improvement of emboli detection compared to traditional methods and has the possibility to be applied in the automatic detection of clinical emboli. 

 

PACS numbers: 43.35, 43.60


 
Copyright © 1996 - 2020 Institute of Acoustics, Chinese Academy of Sciences
No. 21 North 4th Ring Road, Haidian District, 100190 Beijing, China
E-mail: ioa@mail.ioa.ac.cn