Document Detail


A sparse representation method for magnetic resonance spectroscopy quantification.
MedLine Citation:
PMID:  20483699     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper, a sparse representation method is proposed for magnetic resonance spectroscopy (MRS) quantification. An observed MR spectrum is composed of a set of metabolic spectra of interest, a baseline and a noise. To separate the spectra of interest, the a priori knowledge about these spectra, such as signal models, the peak frequencies, and linewidth ranges of different resonances, is first integrated to construct a dictionary. The separation of the spectra of interest is then performed by using a pursuit algorithm to find their sparse representations with respect to the dictionary. For the challenging baseline problem, a wavelet filter is proposed to filter the smooth and broad components of both the observed spectra and the basis functions in the dictionary. The computation of sparse representation can then be carried out by using the remaining data. Simulation results show the good performance of this wavelet filtering-based strategy in separating the overlapping components between the baselines and the spectra of interest, when no appropriate model function for the baseline is available. Quantifications of in vivo brain MR spectra from tumor patients in different stages of progression demonstrate the effectiveness of the proposed method.
Authors:
Yu Guo; Su Ruan; Jérôme Landré; Jean-Marc Constans
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Publication Detail:
Type:  Journal Article     Date:  2010-05-17
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  57     ISSN:  1558-2531     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  2010 Jul 
Date Detail:
Created Date:  2010-07-27     Completed Date:  2010-10-28     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1620-7     Citation Subset:  IM    
Affiliation:
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication, Université de Reims Champagne-Ardenne, Troyes 10000, France. yu.guo@etudiant.univ-reims.fr
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Brain / anatomy & histology
Brain Neoplasms / pathology
Computer Simulation
Humans
Magnetic Resonance Spectroscopy / methods*
Normal Distribution
Phosphorus Isotopes
Signal Processing, Computer-Assisted*
Chemical
Reg. No./Substance:
0/Phosphorus Isotopes

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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