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
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;
Conference_Titel :
Systems, Signal Processing and their Applications (WoSSPA), 2013 8th International Workshop on
Conference_Location :
Algiers
DOI :
10.1109/WoSSPA.2013.6602341