Title :
Water Component Suppression by Empirical Model Decomposition
Author :
Zeng Weiming ; Zhang Shouchun
Author_Institution :
Coll. of Inf. Eng., Shanghai Maritime Univ., Shanghai, China
Abstract :
Water component suppression is critical in proto magnetic resonance spectroscopy quantification analysis. In this paper, we present a new water component suppression method based on empirical model decomposition. Simulated signal experiment and in vivo signal experiment show that the method may have better performance than the classical method based on singular value decomposition.
Keywords :
brain; magnetic resonance spectroscopy; medical signal processing; neurophysiology; physiological models; singular value decomposition; water; classical method; empirical model decomposition; in vivo signal experiment; protomagnetic resonance spectroscopy quantification analysis; simulated signal experiment; singular value decomposition; water component suppression; In vivo; Nuclear magnetic resonance; Protons; Solvents; Spectroscopy; Time frequency analysis;
Conference_Titel :
Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5088-6
DOI :
10.1109/icbbe.2011.5780275