Comparison of blind source separation algorithms for FMRI using a new Matlab toolbox: GIFT

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 pa...

Full description

Saved in:
Bibliographic Details
Published inProceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005 Vol. 5; pp. v/401 - v/404 Vol. 5
Main Authors Correa, N., Adali, T., Yi-Ou Li, Calhoun, V.D.
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 2005
Subjects
Algorithm design and analysis
Blind source separation
Computer languages
Data visualization
Image analysis
Independent component analysis
Magnetic analysis
Magnetic resonance imaging
Performance analysis
Source separation
Online AccessGet full text
ISBN9780780388741
0780388747
ISSN1520-6149
DOI10.1109/ICASSP.2005.1416325

Cover

More Information
Summary: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.
ISBN:9780780388741
0780388747
ISSN:1520-6149
DOI:10.1109/ICASSP.2005.1416325