Premium
Versatile frequency domain fitting using time domain models and prior knowledge
Author(s) -
Slotboom Johannes,
Boesch Chris,
Kreis Roland
Publication year - 1998
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.1910390607
Subject(s) - frequency domain , algorithm , curve fitting , time domain , domain (mathematical analysis) , gaussian , computer science , non linear least squares , nonlinear system , least squares function approximation , mathematics , estimation theory , statistics , machine learning , physics , mathematical analysis , quantum mechanics , estimator , computer vision
An iterative nonlinear least‐squares fitting algorithm in the frequency domain using time domain models for quantification of complex frequency domain MR spectra is presented. The algorithm allows incorporation of prior knowledge and has both the advantage of time‐domain fitting with respect to handling the problem of missing data points and truncated data sets and of frequency‐domain fitting with respect to multiple frequency‐selective fitting. The described algorithm can handle, in addition to Lorentzian and Gaussian line‐shapes, Voigt and nonanalytic lineshapes. The program allows the user the design of his own fitting strategy to optimize the probability of reaching the global least‐squares minimum. The application of the fitting program is illustrated with examples from in vivo 1 H– 31 P‐, and 13 C‐MR spectroscopy.