Automatic frequency alignment and quantitation of single resonances in multiple magnetic resonance spectra via complex principal component analysis.
Several algorithms for automatic frequency alignment and quantitation of single resonances in multiple magnetic resonance (MR) spectra are investigated. First, a careful comparison between the complex principal component analysis (PCA) and the Hankel total least squares-based methods for quantifying the resonances in the spectral sets of magnetic resonance spectroscopy imaging (MRSI) spectra is presented. Afterward, we discuss a method based on complex PCA plus linear regression and a method based on cross correlation of the magnitude spectra for correcting frequency shifts of resonances in sets of MR spectra. Their advantages and limitations are demonstrated on simulated MR data sets as well as on an in vivo MRSI data set of the human brain.
Van Huffel
Sabine
S
Department of Electrical Engineering, Katholieke Universiteit Leuven, SCD-SISTA, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. sabine.vanhuffel@esat.kuleuven.ac.be
Wang
Yu
Y
Vanhamme
Leentje
L
Van Hecke
Paul
P
D001921:Brain / Q000033:anatomy & histology; D003198:Computer Simulation; D006801:Humans; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*