A Matlab toolbox for fMRI artifact reduction using ICA and global decision trees described in
J. Tohka , K. Foerde, A.R. Aron, S. M. Tom, A.W. Toga, and R.A. Poldrack. Automatic Independent Component Labeling for Artifact Removal in fMRI. NeuroImage, 39(3):1227-45, 2008. [Software] [Pubmed Central version]
To use this package you will also need NiFTI tools which can be downloaded here
The software automatically classifies fMRI independent components to "signal" and "noise". Note that this software is from 2008!
(Main) differences between new versions and the fmri_ica_classify 1.1 and fmri_ica_training 1.2:
fmri_ica_classify version 1.1.1 and fmri_ica_training version 1.2.1: These have been updated to use load_untouch_nii.m (see NiFTI tools page for details about differences between load_nii.m and load_untouch_nii.m). However, since the artifact reduction tool does not modify and/or write any image files (it rather relies on FSL programs to do the actual processing), it is not dangerous to use an older version. Thus, those who have crafted the tool to suit their needs should probably continue to use the old versions (the version 1.1 of the classifier and the version 1.2 of the classifier training).
fmri_ica_classify version 1.1.2: This was updated to use fsl_regfilt for denoising to conform to versions 3.x of the melodic software. The end result should be the same as with the older versions which used melodic -f for the same purpose. Note however that file naming conventions are different between fsl_regfilt and melodic -f . Also, the file masking seems to be different (fsl_regfilt seems not to mask files as melodic -f did).
Important : Please read the related paper and manuals. Only preliminary testing has been done, so bugs may exist...