interfaces.nipy.preprocess¶
ComputeMask¶
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¶
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 = list(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: (a list of items which are an existing file name)
File to realign
tr: (a float)
TR in seconds
[Optional]
between_loops: (a list of items which are an integer (int or long),
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: (a list of items which are an integer (int or long), nipype
default value: [5])
loops within each run
slice_order: (a list of items which are an integer (int or long))
0 based slice order. This would be equivalent to
enteringnp.argsort(spm_slice_order) for this field. This
effectsinterleaved acquisition. This field will be deprecated
infuture Nipy releases and be replaced by actual sliceacquisition
times.
requires: time_interp
speedup: (a list of items which are an integer (int or long), 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: (a list of items which are an existing file name)
Realigned files
par_file: (a list of items which are an existing file name)
Motion parameter files
SpaceTimeRealigner¶
Simultaneous motion and slice timing correction algorithm
If slice_times is not specified, this algorithm performs spatial motion correction
This interface wraps nipy’s SpaceTimeRealign algorithm [Roche2011] or simply the SpatialRealign algorithm when timing info is not provided.
Examples¶
>>> from nipype.interfaces.nipy import SpaceTimeRealigner
>>> #Run spatial realignment only
>>> realigner = SpaceTimeRealigner()
>>> realigner.inputs.in_file = ['functional.nii']
>>> res = realigner.run()
>>> realigner = SpaceTimeRealigner()
>>> realigner.inputs.in_file = ['functional.nii']
>>> realigner.inputs.tr = 2
>>> realigner.inputs.slice_times = list(range(0, 3, 67))
>>> realigner.inputs.slice_info = 2
>>> res = realigner.run()
References¶
| [Roche2011] | 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: (a list of items which are an existing file name)
File to realign
[Optional]
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
slice_info: (an integer (int or long) or a list of items which are
any value)
Single integer or length 2 sequence If int, the axis in `images`
that is the slice axis. In a 4D image, this will often be axis = 2.
If a 2 sequence, then elements are ``(slice_axis,
slice_direction)``, where ``slice_axis`` is the slice axis in the
image as above, and ``slice_direction`` is 1 if the slices were
acquired slice 0 first, slice -1 last, or -1 if acquired slice -1
first, slice 0 last. If `slice_info` is an int, assume
``slice_direction`` == 1.
requires: slice_times
slice_times: (a list of items which are a float or 'asc_alt_2' or
'asc_alt_2_1' or 'asc_alt_half' or 'asc_alt_siemens' or 'ascending'
or 'desc_alt_2' or 'desc_alt_half' or 'descending')
Actual slice acquisition times.
tr: (a float)
TR in seconds
requires: slice_times
Outputs:
out_file: (a list of items which are an existing file name)
Realigned files
par_file: (a list of items which are an existing file name)
Motion parameter files. Angles are not euler angles
Trim¶
Simple interface to trim a few volumes from a 4d fmri nifti file
Examples¶
>>> from nipype.interfaces.nipy.preprocess import Trim
>>> trim = Trim()
>>> trim.inputs.in_file = 'functional.nii'
>>> trim.inputs.begin_index = 3 # remove 3 first volumes
>>> res = trim.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
EPI image to trim
[Optional]
begin_index: (an integer (int or long), nipype default value: 0)
first volume
end_index: (an integer (int or long), nipype default value: 0)
last volume indexed as in python (and 0 for last)
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
out_file: (a file name)
output filename
suffix: (a string, nipype default value: _trim)
suffix for out_file to use if no out_file provided
Outputs:
out_file: (an existing file name)