Code: http://github.com/nipy/nipype/blob/master/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)
Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/nipy/preprocess.py#L102
Simultaneous motion and slice timing correction algorithm
This interface wraps nipy’s FmriRealign4d algorithm [1].
>>> from nipype.interfaces.nipy.preprocess import FmriRealign4d
>>> realigner = FmriRealign4d()
>>> realigner.inputs.in_file = ['functional.nii']
>>> realigner.inputs.tr = 2
>>> realigner.inputs.slice_order = 'ascending'
>>> realigner.inputs.interleaved = True
>>> res = realigner.run()
[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
interleaved: (a boolean)
True if interleaved
slice_order: (a list of items which are an integer or 'ascending' or 'descending')
slice order
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
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: (a boolean, nipype default value: True)
Assume smooth changes across time e.g., fmri series
tr_slices: (a float)
TR slices
Outputs:
out_file
Realigned files
par_file
Motion parameter files