• 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