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interfaces.nipy.preprocess

ComputeMask

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/nipy/preprocess.py#L40

Inputs:

[Mandatory]
mean_volume: (an existing file name)
        mean EPI image, used to compute the threshold for the mask

[Optional]
M: (a float)
        upper fraction of the histogram to be discarded
cc: (a boolean)
        Keep only the largest connected component
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
m: (a float)
        lower fraction of the histogram to be discarded
reference_volume: (an existing file name)
        reference volume used to compute the mask. If none is give, the mean volume is used.

Outputs:

brain_mask: (an existing file name)

FmriRealign4d

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/nipy/preprocess.py#L109

Simultaneous motion and slice timing correction algorithm

This interface wraps nipy’s FmriRealign4d algorithm [1].

Examples

>>> from nipype.interfaces.nipy.preprocess import FmriRealign4d
>>> realigner = FmriRealign4d()
>>> realigner.inputs.in_file = ['functional.nii']
>>> realigner.inputs.tr = 2
>>> realigner.inputs.slice_order = range(0,67)
>>> res = realigner.run() 

References

[1]Roche A. A four-dimensional registration algorithm with application to joint correction of motion and slice timing in fMRI. IEEE Trans Med Imaging. 2011 Aug;30(8):1546-54. DOI.

Inputs:

[Mandatory]
in_file
        File to realign
tr: (a float)
        TR in seconds

[Optional]
between_loops: (an integer, nipype default value: [5])
        loops used to                                                           realign
        different                                                           runs
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
loops: (an integer, nipype default value: [5])
        loops within each run
slice_order: (a list of items which are an integer)
        0 based slice order
        requires: time_interp
speedup: (an integer, nipype default value: [5])
        successive image                                   sub-sampling factors
        for acceleration
start: (a float, nipype default value: 0.0)
        time offset into TR to align slices to
time_interp: (True)
        Assume smooth changes across time e.g.,                     fmri series. If you don't
        want slice timing                      correction set this to undefined
        requires: slice_order
tr_slices: (a float)
        TR slices
        requires: time_interp

Outputs:

out_file: (an existing file name)
        Realigned files
par_file: (an existing file name)
        Motion parameter files