Frequency-selective MRS data quantification with frequency prior knowledge. Export

@article{citeulike:1104616, abstract = {Various signal processing techniques have been proposed to improve spectral estimation of closely spaced sinusoids in the presence of noise. This paper exploits frequency prior knowledge information to extract single peaks in magnetic resonance spectra, corresponding to metabolites of interest, by means of a highly selective finite impulse response filter. Thereafter the estimation of the parameters of the peaks is carried out using a singular-value-decomposition-based method known as HTLS. The new technique improves the performance of fully automated magnetic resonance spectroscopy data quantification when frequency prior knowledge is available.}, address = {Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kard. Mercierlaan 94, Leuven, 3001, Belgium.}, author = {Dologlou, I. and Van Huffel, S. and Van Ormondt, D.}, citeulike-article-id = {1104616}, citeulike-linkout-0 = {http://dx.doi.org/10.1006/jmre.1997.1315}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/9500900}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=9500900}, doi = {10.1006/jmre.1997.1315}, issn = {1090-7807}, journal = {J Magn Reson}, keywords = {frequency, mrs, selection}, month = {February}, number = {2}, pages = {238--243}, posted-at = {2007-02-13 08:16:30}, priority = {4}, title = {Frequency-selective MRS data quantification with frequency prior knowledge.}, url = {http://dx.doi.org/10.1006/jmre.1997.1315}, volume = {130}, year = {1998} }

TY - JOUR ID - citeulike:1104616 L3 - citeulike-article-id:1104616 N2 - Various signal processing techniques have been proposed to improve spectral estimation of closely spaced sinusoids in the presence of noise. This paper exploits frequency prior knowledge information to extract single peaks in magnetic resonance spectra, corresponding to metabolites of interest, by means of a highly selective finite impulse response filter. Thereafter the estimation of the parameters of the peaks is carried out using a singular-value-decomposition-based method known as HTLS. The new technique improves the performance of fully automated magnetic resonance spectroscopy data quantification when frequency prior knowledge is available. IS - 2 JF - J Magn Reson SN - 1090-7807 AD - Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kard. Mercierlaan 94, Leuven, 3001, Belgium. EP - 243 TI - Frequency-selective MRS data quantification with frequency prior knowledge. VL - 130 SP - 238 KW - frequency KW - mrs KW - selection AU - Dologlou, I AU - Van Huffel, S AU - Van Ormondt, D PY - 1998/02// UR - http://dx.doi.org/10.1006/jmre.1997.1315 ER -