Comparison of blind source separation algorithms for FMRI using a new Matlab toolbox: GIFT
Proceedings.(ICASSP'05). IEEE International Conference on …, 2005•ieeexplore.ieee.org
We study the performance of five blind source separation (BSS) algorithms when applied to
analysis of functional magnetic resonance imaging (fMRI) data. We introduce a Matlab-
based toolbox, the group ICA of fMRI toolbox (GIFT), which enables analysis of groups of
subjects using BSS algorithms, in particular those based on independent component
analysis (ICA). We use the visualization and computational tools included in GIFT to
quantitatively analyze the performance of different BSS algorithms for fMRI analysis and …
analysis of functional magnetic resonance imaging (fMRI) data. We introduce a Matlab-
based toolbox, the group ICA of fMRI toolbox (GIFT), which enables analysis of groups of
subjects using BSS algorithms, in particular those based on independent component
analysis (ICA). We use the visualization and computational tools included in GIFT to
quantitatively analyze the performance of different BSS algorithms for fMRI analysis and …
We study the performance of five blind source separation (BSS) algorithms when applied to analysis of functional magnetic resonance imaging (fMRI) data. We introduce a Matlab-based toolbox, the group ICA of fMRI toolbox (GIFT), which enables analysis of groups of subjects using BSS algorithms, in particular those based on independent component analysis (ICA). We use the visualization and computational tools included in GIFT to quantitatively analyze the performance of different BSS algorithms for fMRI analysis and discuss the results.
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