DocumentCode
3086483
Title
Empirical mode decomposition based support vector machines for microemboli classification
Author
Ferroudji, Karim ; Benoudjit, N. ; Bouakaz, Adnan
Author_Institution
Electron. Dept., Univ. of Batna, Batna, Algeria
fYear
2013
fDate
12-15 May 2013
Firstpage
84
Lastpage
88
Abstract
The classification of circulating microemboli, in the bloodstream, as gaseous or particulate matter is vital for selecting appropriate treatment for patients. Until now, Doppler techniques have shown some limitations to determine clearly the nature of circulating microemboli. The traditional techniques are largely based on the Fourier analysis. In this paper we present new emboli detection method based on Empirical mode decomposition and support vector machine using Radio Frequency (RF) signal instead of Doppler signals.
Keywords
Doppler effect; haemodynamics; image classification; medical image processing; patient treatment; radiofrequency imaging; support vector machines; Doppler signals; Doppler techniques; Fourier analysis; RF signal; bloodstream; empirical mode decomposition-based support vector machines; gaseous matter; microemboli, circulating classification; particulate matter; patient treatment; radiofrequency signal; support vector machine; Doppler effect; Empirical mode decomposition; Kernel; RF signals; Solids; Support vector machines; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
Conference_Location
Algiers
Type
conf
DOI
10.1109/WoSSPA.2013.6602341
Filename
6602341
Link To Document