title: Frequency-selective quantification of biomedical magnetic resonance spectroscopy data.
abstract: In this paper the possibility of obtaining accurate estimates of parameters of selected peaks in the presence of unknown or uninteresting spectral features in biomedical magnetic resonance spectroscopy (MRS) signals is investigated. This problem is denoted by frequency-selective parameter estimation. A new time-domain technique based on maximum-phase finite impulse response (FIR) filters is presented. The proposed method is compared to a number of existing approaches: the application of a weighting function in the time domain, frequency domain fitting using a polynomial baseline, and the time-domain HSVD filter method. The ease of use and low computational complexity of the FIR filter method make it an attractive approach for frequency-selective parameter estimation. The methods are validated using simulations of relevant (13)C and (31)P MRS examples.
authors.affiliation: Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kard. Mercierlaan 94, Leuven, 3001, Belgium. leentje.vanhamme@esat.kuleuven.ac.be
authors.forename: L
authors.initials: L
authors.lastname: Vanhamme
authors.forename: T
authors.initials: T
authors.lastname: Sundin
authors.forename: P
authors.initials: P
authors.lastname: Van Hecke
authors.forename: S
authors.initials: S
authors.lastname: Van Huffel
authors.forename: R
authors.initials: R
authors.lastname: Pintelon
mesh_terms: D000255:Adenosine Triphosphate / Q000032:analysis; D000273:Adipose Tissue / Q000737:chemistry; D000818:Animals; D002247:Carbon Isotopes; D006801:Humans; D008099:Liver / Q000737:chemistry; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D051381:Rats
chemical_list: D002247:Carbon Isotopes; D000255:Adenosine Triphosphate