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# interfaces.fsl.aroma

## ICA_AROMA

Link to code

Wraps command ICA_AROMA.py

Interface for the ICA_AROMA.py script.

ICA-AROMA (i.e. ‘ICA-based Automatic Removal Of Motion Artifacts’) concerns a data-driven method to identify and remove motion-related independent components from fMRI data. To that end it exploits a small, but robust set of theoretically motivated features, preventing the need for classifier re-training and therefore providing direct and easy applicability.

See link for further documentation: https://github.com/rhr-pruim/ICA-AROMA

### Example

    >>> from nipype.interfaces.fsl import ICA_AROMA
    >>> from nipype.testing import example_data
    >>> AROMA_obj = ICA_AROMA()
    >>> AROMA_obj.inputs.in_file = 'functional.nii'
    >>> AROMA_obj.inputs.mat_file = 'func_to_struct.mat'
    >>> AROMA_obj.inputs.fnirt_warp_file = 'warpfield.nii'
    >>> AROMA_obj.inputs.motion_parameters = 'fsl_mcflirt_movpar.txt'
    >>> AROMA_obj.inputs.mask = 'mask.nii.gz'
    >>> AROMA_obj.inputs.denoise_type = 'both'
    >>> AROMA_obj.inputs.out_dir = 'ICA_testout'
    >>> AROMA_obj.cmdline
    'ICA_AROMA.py -den both -warp warpfield.nii -i functional.nii -m mask.nii.gz -affmat func_to_struct.mat -mc fsl_mcflirt_movpar.txt -o ICA_testout'

Inputs:

    [Mandatory]
    denoise_type: (u'nonaggr' or u'aggr' or u'both' or u'no', nipype
             default value: nonaggr)
            Type of denoising strategy:
            -no: only classification, no denoising
            -nonaggr (default): non-aggresssive denoising, i.e. partial
            component regression
            -aggr: aggressive denoising, i.e. full component regression
            -both: both aggressive and non-aggressive denoising (two outputs)
            flag: -den %s
    feat_dir: (an existing directory name)
            If a feat directory exists and temporal filtering has not been run
            yet, ICA_AROMA can use the files in this directory.
            flag: -feat %s
            mutually_exclusive: in_file, mat_file, fnirt_warp_file,
             motion_parameters
    in_file: (an existing file name)
            volume to be denoised
            flag: -i %s
            mutually_exclusive: feat_dir
    motion_parameters: (an existing file name)
            motion parameters file
            flag: -mc %s
            mutually_exclusive: feat_dir

    [Optional]
    TR: (a float)
            TR in seconds. If this is not specified the TR will be extracted
            from the header of the fMRI nifti file.
            flag: -tr %.3f
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    dim: (an integer (int or long))
            Dimensionality reduction when running MELODIC (defualt is automatic
            estimation)
            flag: -dim %d
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    fnirt_warp_file: (an existing file name)
            File name of the warp-file describing the non-linear registration
            (e.g. FSL FNIRT) of the structural data to MNI152 space (.nii.gz)
            flag: -warp %s
            mutually_exclusive: feat_dir
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    mask: (an existing file name)
            path/name volume mask
            flag: -m %s
            mutually_exclusive: feat_dir
    mat_file: (an existing file name)
            path/name of the mat-file describing the affine registration (e.g.
            FSL FLIRT) of the functional data to structural space (.mat file)
            flag: -affmat %s
            mutually_exclusive: feat_dir
    melodic_dir: (an existing directory name)
            path to MELODIC directory if MELODIC has already been run
            flag: -meldir %s
    out_dir: (a directory name)
            output directory
            flag: -o %s
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

Outputs:

    aggr_denoised_file: (an existing file name)
            if generated: aggressively denoised volume
    nonaggr_denoised_file: (an existing file name)
            if generated: non aggressively denoised volume
    out_dir: (an existing directory name)
            directory contains (in addition to the denoised files): melodic.ica
            + classified_motion_components + classification_overview +
            feature_scores + melodic_ic_mni)