Ravi Kalyanam, David Boutte, Chuck Gasparovic, Kent E. Hutchison and Vince D. Calhoun Group independent component analysis of MR spectra Brain and Behavior 3
This study investigates the potential of independent component analysis (ICA) to provide a data driven approach for group level analysis of magnetic resonance (MR) spectra. A comparative evaluation of the ICA and LCModel methods in analyzing noise- and artifacts-free simulated data sets of known compositions and single voxel in vivo spectra from multiple subjects is presented. The results provide evidence that ICA is a promising technique for decomposing MR spectral data into components resembling metabolite resonances, and therefore has the potential to provide a data-driven alternative to the use of metabolite concentrations, in making group comparisons.
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