Multiple wavelet denoising for embolic signal enhancement

被引:1
作者
Marvasti, Salman [1 ]
Ghandi, Mahmoud [2 ]
Marvasti, Farokh [3 ]
Markus, Hugh S. [4 ]
Gillies, Duncan [5 ]
机构
[1] Imperial Coll, London, England
[2] Sharif Univ Technol, ACRI, Tehran, Iran
[3] Adv Commun Res Inst, EE Dept, Tehran, Iran
[4] St Georges Univ London, Ctr Clin Neurosci, London, England
[5] Imperial Coll, Visual Informat Proc Grp, London, England
来源
ICT-MICC: 2007 IEEE INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND MALAYSIA INTERNATIONAL CONFERENCE ON COMMUNICATIONS, VOLS 1 AND 2, PROCEEDINGS | 2007年
基金
英国工程与自然科学研究理事会;
关键词
wavelets; denoising; adaptive filtering; transcranial Doppler ultrasound; automatic detection; cerebral embolism;
D O I
10.1109/ICTMICC.2007.4448575
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Transcranial Doppler ultrasound can be used to detect circulating cerebral emboli. Embolic signals have characteristic transient chirps suitable for wavelet analysis. We have implemented and evaluated the first online selective selective wavelet transient enhancement filter to amplify embolic signals in a preprocessing system. Our approach is similar to wavelet de-noising for signal enhancement, but, in order to retain blood flow information, we do not use traditional threshold methods. The selective wavelet amplifier uses the matched filter properties of wavelets to enhance embolic signals significantly and improve classification performance using a novel noise tolerant approach. Even the smallest embolic signals are enhanced. We show an increase of over 2dB (on average) in embolic signal strength and a significant improvement in detection accuracy when our filter is applied both to a commercially available detection system and an in house frequency based detection system. The implementation of the filter is simplified by using. an optimized matrix form. The block matrix form is significantly faster than the normal recursive discrete wavelet transform implementation(6).
引用
收藏
页码:658 / +
页数:3
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