Embolic Doppler ultrasound signal detection using modified dual tree complex wavelet transform

Gorkem Serbes*, Nizamettin Aydin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Asymptomatic circulating cerebral emboli, which are particles larger than red blood cells, can be detected by Doppler ultrasound. Embolic signals are short duration transient like signals. Embolic signals can be extracted from quadrature Doppler signals, which are obtained at the end of quadrature demodulation. The wavelet transform is an ideal method for analysis and detection of such signals by optimizing time-frequency resolution. In literature systems employing discrete wavelet transform (DWT) for detecting embolic signals exist. Dual-tree complex wavelet transform (DTCWT), which is a shift invariant transform with limited redundancy, is an improved version of DWT. Conventionally, prior to applying the DTCWT to an quadrature signal, first the quadrature signal must be decoded into forward and reverse signals and then two DTCWT should be applied. However, modified dual-tree complex wavelet transform (MDTCWT), which reduces the computational complexity compared to conventional algorithm, can be used. In this study a new emboli detection system based on MDTCWT is proposed. In detection algorithm, embolic signals and artifact signals were decomposed to nine scales and different features were extracted from each scale. Then for each scale, by using extracted features a new feature vector was created and these feature vectors are fed into support vector machines individually and the comparative results of individual feature sets are proposed.

Original languageEnglish
Title of host publicationProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics
Subtitle of host publicationGlobal Grand Challenge of Health Informatics, BHI 2012
Pages945-947
Number of pages3
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering - Hong Kong and Shenzhen, China
Duration: 2 Jan 20127 Jan 2012

Publication series

NameProceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012

Conference

ConferenceIEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering
Country/TerritoryChina
CityHong Kong and Shenzhen
Period2/01/127/01/12

Fingerprint

Dive into the research topics of 'Embolic Doppler ultrasound signal detection using modified dual tree complex wavelet transform'. Together they form a unique fingerprint.

Cite this