Title :
Analysis of Magnetic Resonance Spectroscopic signals with data-based autocorrelation wavelets
Author :
Schuck, A. ; Lemke, C. ; Suvichakorn, A. ; Antoine, J.-P.
Author_Institution :
Electr. Eng. Dept. (DELET), Fed. Univ. of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
A new class of wavelet functions called data-based autocorrelation wavelets is developed for analyzing Magnetic Resonance Spectroscopic (MRS) signals by means of the continuous wavelet transform (CWT), instead of the traditional wavelet like Morlet wavelet. These new wavelets are derived from the normalized autocorrelation function from metabolite data and then used for detecting the presence of a given metabolite in a signal with a presence of many different components and finally for quantifying some of its parameters.
Keywords :
biomagnetism; magnetic resonance spectroscopy; medical signal processing; molecular biophysics; wavelet transforms; continuous wavelet transform; data-based autocorrelation wavelet; magnetic resonance spectroscopic signal analysis; metabolite data; normalized autocorrelation function; Continuous wavelet transforms; Correlation; Damping; Wavelet analysis; Wavelet domain; Algorithms; Data Interpretation, Statistical; Magnetic Resonance Spectroscopy; Statistics as Topic; Wavelet Analysis;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5628034
