interfaces.fsl.preprocess¶
ApplyWarp¶
Wraps command applywarp
Use FSL’s applywarp to apply the results of a FNIRT registration
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> aw = fsl.ApplyWarp()
>>> aw.inputs.in_file = example_data('structural.nii')
>>> aw.inputs.ref_file = example_data('mni.nii')
>>> aw.inputs.field_file = 'my_coefficients_filed.nii'
>>> res = aw.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
image to be warped
flag: --in=%s, position: 0
ref_file: (an existing file name)
reference image
flag: --ref=%s, position: 1
[Optional]
abswarp: (a boolean)
treat warp field as absolute: x' = w(x)
flag: --abs
mutually_exclusive: relwarp
args: (a string)
Additional parameters to the command
flag: %s
datatype: ('char' or 'short' or 'int' or 'float' or 'double')
Force output data type [char short int float double].
flag: --datatype=%s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
field_file: (an existing file name)
file containing warp field
flag: --warp=%s
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
interp: ('nn' or 'trilinear' or 'sinc' or 'spline')
interpolation method
flag: --interp=%s, position: -2
mask_file: (an existing file name)
filename for mask image (in reference space)
flag: --mask=%s
out_file: (a file name)
output filename
flag: --out=%s, position: 2
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
postmat: (an existing file name)
filename for post-transform (affine matrix)
flag: --postmat=%s
premat: (an existing file name)
filename for pre-transform (affine matrix)
flag: --premat=%s
relwarp: (a boolean)
treat warp field as relative: x' = x + w(x)
flag: --rel, position: -1
mutually_exclusive: abswarp
superlevel: ('a' or an integer (int or long))
level of intermediary supersampling, a for 'automatic' or integer
level. Default = 2
flag: --superlevel=%s
supersample: (a boolean)
intermediary supersampling of output, default is off
flag: --super
terminal_output: ('stream' or 'allatonce' or 'file' or '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:
out_file: (an existing file name)
Warped output file
ApplyXfm¶
Wraps command flirt
Currently just a light wrapper around FLIRT, with no modifications
ApplyXfm is used to apply an existing tranform to an image
Examples¶
>>> import nipype.interfaces.fsl as fsl
>>> from nipype.testing import example_data
>>> applyxfm = fsl.ApplyXfm()
>>> applyxfm.inputs.in_file = example_data('structural.nii')
>>> applyxfm.inputs.in_matrix_file = example_data('trans.mat')
>>> applyxfm.inputs.out_file = 'newfile.nii'
>>> applyxfm.inputs.reference = example_data('mni.nii')
>>> applyxfm.inputs.apply_xfm = True
>>> result = applyxfm.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input file
flag: -in %s, position: 0
reference: (an existing file name)
reference file
flag: -ref %s, position: 1
[Optional]
angle_rep: ('quaternion' or 'euler')
representation of rotation angles
flag: -anglerep %s
apply_isoxfm: (a float)
as applyxfm but forces isotropic resampling
flag: -applyisoxfm %f
mutually_exclusive: apply_xfm
apply_xfm: (a boolean, nipype default value: True)
apply transformation supplied by in_matrix_file
flag: -applyxfm
requires: in_matrix_file
args: (a string)
Additional parameters to the command
flag: %s
bbrslope: (a float)
value of bbr slope
flag: -bbrslope %f
bbrtype: ('signed' or 'global_abs' or 'local_abs')
type of bbr cost function: signed [default], global_abs, local_abs
flag: -bbrtype %s
bgvalue: (a float)
use specified background value for points outside FOV
flag: -setbackground %f
bins: (an integer (int or long))
number of histogram bins
flag: -bins %d
coarse_search: (an integer (int or long))
coarse search delta angle
flag: -coarsesearch %d
cost: ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or
'leastsq' or 'labeldiff' or 'bbr')
cost function
flag: -cost %s
cost_func: ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or
'leastsq' or 'labeldiff' or 'bbr')
cost function
flag: -searchcost %s
datatype: ('char' or 'short' or 'int' or 'float' or 'double')
force output data type
flag: -datatype %s
display_init: (a boolean)
display initial matrix
flag: -displayinit
dof: (an integer (int or long))
number of transform degrees of freedom
flag: -dof %d
echospacing: (a float)
value of EPI echo spacing - units of seconds
flag: -echospacing %f
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
fieldmap: (a file name)
fieldmap image in rads/s - must be already registered to the
reference image
flag: -fieldmap %s
fieldmapmask: (a file name)
mask for fieldmap image
flag: -fieldmapmask %s
fine_search: (an integer (int or long))
fine search delta angle
flag: -finesearch %d
force_scaling: (a boolean)
force rescaling even for low-res images
flag: -forcescaling
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
in_matrix_file: (a file name)
input 4x4 affine matrix
flag: -init %s
in_weight: (an existing file name)
File for input weighting volume
flag: -inweight %s
interp: ('trilinear' or 'nearestneighbour' or 'sinc' or 'spline')
final interpolation method used in reslicing
flag: -interp %s
min_sampling: (a float)
set minimum voxel dimension for sampling
flag: -minsampling %f
no_clamp: (a boolean)
do not use intensity clamping
flag: -noclamp
no_resample: (a boolean)
do not change input sampling
flag: -noresample
no_resample_blur: (a boolean)
do not use blurring on downsampling
flag: -noresampblur
no_search: (a boolean)
set all angular searches to ranges 0 to 0
flag: -nosearch
out_file: (a file name)
registered output file
flag: -out %s, position: 2
out_log: (a file name)
output log
requires: save_log
out_matrix_file: (a file name)
output affine matrix in 4x4 asciii format
flag: -omat %s, position: 3
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
padding_size: (an integer (int or long))
for applyxfm: interpolates outside image by size
flag: -paddingsize %d
pedir: (an integer (int or long))
phase encode direction of EPI - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z
flag: -pedir %d
ref_weight: (an existing file name)
File for reference weighting volume
flag: -refweight %s
rigid2D: (a boolean)
use 2D rigid body mode - ignores dof
flag: -2D
save_log: (a boolean)
save to log file
schedule: (an existing file name)
replaces default schedule
flag: -schedule %s
searchr_x: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along x-axis, in degrees
flag: -searchrx %s
searchr_y: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along y-axis, in degrees
flag: -searchry %s
searchr_z: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along z-axis, in degrees
flag: -searchrz %s
sinc_width: (an integer (int or long))
full-width in voxels
flag: -sincwidth %d
sinc_window: ('rectangular' or 'hanning' or 'blackman')
sinc window
flag: -sincwindow %s
terminal_output: ('stream' or 'allatonce' or 'file' or '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
uses_qform: (a boolean)
initialize using sform or qform
flag: -usesqform
verbose: (an integer (int or long))
verbose mode, 0 is least
flag: -verbose %d
wm_seg: (a file name)
white matter segmentation volume needed by BBR cost function
flag: -wmseg %s
wmcoords: (a file name)
white matter boundary coordinates for BBR cost function
flag: -wmcoords %s
wmnorms: (a file name)
white matter boundary normals for BBR cost function
flag: -wmnorms %s
Outputs:
out_file: (an existing file name)
path/name of registered file (if generated)
out_log: (a file name)
path/name of output log (if generated)
out_matrix_file: (an existing file name)
path/name of calculated affine transform (if generated)
BET¶
Wraps command bet
Use FSL BET command for skull stripping.
For complete details, see the BET Documentation.
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> btr = fsl.BET()
>>> btr.inputs.in_file = example_data('structural.nii')
>>> btr.inputs.frac = 0.7
>>> res = btr.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input file to skull strip
flag: %s, position: 0
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
center: (a list of at most 3 items which are an integer (int or
long))
center of gravity in voxels
flag: -c %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
frac: (a float)
fractional intensity threshold
flag: -f %.2f
functional: (a boolean)
apply to 4D fMRI data
flag: -F
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
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: (a boolean)
create binary mask image
flag: -m
mesh: (a boolean)
generate a vtk mesh brain surface
flag: -e
no_output: (a boolean)
Don't generate segmented output
flag: -n
out_file: (a file name)
name of output skull stripped image
flag: %s, position: 1
outline: (a boolean)
create surface outline image
flag: -o
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
padding: (a boolean)
improve BET if FOV is very small in Z (by temporarily padding end
slices)
flag: -Z
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
radius: (an integer (int or long))
head radius
flag: -r %d
reduce_bias: (a boolean)
bias field and neck cleanup
flag: -B
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
remove_eyes: (a boolean)
eye & optic nerve cleanup (can be useful in SIENA)
flag: -S
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
robust: (a boolean)
robust brain centre estimation (iterates BET several times)
flag: -R
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
skull: (a boolean)
create skull image
flag: -s
surfaces: (a boolean)
run bet2 and then betsurf to get additional skull and scalp surfaces
(includes registrations)
flag: -A
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
t2_guided: (a file name)
as with creating surfaces, when also feeding in non-brain-extracted
T2 (includes registrations)
flag: -A2 %s
mutually_exclusive: functional, reduce_bias, robust, padding,
remove_eyes, surfaces, t2_guided
terminal_output: ('stream' or 'allatonce' or 'file' or '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
threshold: (a boolean)
apply thresholding to segmented brain image and mask
flag: -t
vertical_gradient: (a float)
vertical gradient in fractional intensity threshold (-1, 1)
flag: -g %.2f
Outputs:
inskull_mask_file: (a file name)
path/name of inskull mask (if generated)
inskull_mesh_file: (a file name)
path/name of inskull mesh outline (if generated)
mask_file: (a file name)
path/name of binary brain mask (if generated)
meshfile: (a file name)
path/name of vtk mesh file (if generated)
out_file: (a file name)
path/name of skullstripped file (if generated)
outline_file: (a file name)
path/name of outline file (if generated)
outskin_mask_file: (a file name)
path/name of outskin mask (if generated)
outskin_mesh_file: (a file name)
path/name of outskin mesh outline (if generated)
outskull_mask_file: (a file name)
path/name of outskull mask (if generated)
outskull_mesh_file: (a file name)
path/name of outskull mesh outline (if generated)
skull_mask_file: (a file name)
path/name of skull mask (if generated)
FAST¶
Wraps command fast
Use FSL FAST for segmenting and bias correction.
For complete details, see the FAST Documentation.
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
Assign options through the inputs attribute:
>>> fastr = fsl.FAST()
>>> fastr.inputs.in_files = example_data('structural.nii')
>>> out = fastr.run()
Inputs:
[Mandatory]
in_files: (a list of items which are an existing file name)
image, or multi-channel set of images, to be segmented
flag: %s, position: -1
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
bias_iters: (1 <= an integer <= 10)
number of main-loop iterations during bias-field removal
flag: -I %d
bias_lowpass: (4 <= an integer <= 40)
bias field smoothing extent (FWHM) in mm
flag: -l %d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
hyper: (0.0 <= a floating point number <= 1.0)
segmentation spatial smoothness
flag: -H %.2f
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
img_type: (1 or 2 or 3)
int specifying type of image: (1 = T1, 2 = T2, 3 = PD)
flag: -t %d
init_seg_smooth: (0.0001 <= a floating point number <= 0.1)
initial segmentation spatial smoothness (during bias field
estimation)
flag: -f %.3f
init_transform: (an existing file name)
<standard2input.mat> initialise using priors
flag: -a %s
iters_afterbias: (1 <= an integer <= 20)
number of main-loop iterations after bias-field removal
flag: -O %d
manual_seg: (an existing file name)
Filename containing intensities
flag: -s %s
mixel_smooth: (0.0 <= a floating point number <= 1.0)
spatial smoothness for mixeltype
flag: -R %.2f
no_bias: (a boolean)
do not remove bias field
flag: -N
no_pve: (a boolean)
turn off PVE (partial volume estimation)
flag: --nopve
number_classes: (1 <= an integer <= 10)
number of tissue-type classes
flag: -n %d
other_priors: (a list of from 3 to 3 items which are a file name)
alternative prior images
flag: -A %s
out_basename: (a file name)
base name of output files
flag: -o %s
output_biascorrected: (a boolean)
output restored image (bias-corrected image)
flag: -B
output_biasfield: (a boolean)
output estimated bias field
flag: -b
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
probability_maps: (a boolean)
outputs individual probability maps
flag: -p
segment_iters: (1 <= an integer <= 50)
number of segmentation-initialisation iterations
flag: -W %d
segments: (a boolean)
outputs a separate binary image for each tissue type
flag: -g
terminal_output: ('stream' or 'allatonce' or 'file' or '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
use_priors: (a boolean)
use priors throughout
flag: -P
verbose: (a boolean)
switch on diagnostic messages
flag: -v
Outputs:
bias_field: (a list of items which are a file name)
mixeltype: (a file name)
path/name of mixeltype volume file _mixeltype
partial_volume_files: (a list of items which are a file name)
partial_volume_map: (a file name)
path/name of partial volume file _pveseg
probability_maps: (a list of items which are a file name)
restored_image: (a list of items which are a file name)
tissue_class_files: (a list of items which are a file name)
tissue_class_map: (an existing file name)
path/name of binary segmented volume file one val for each class
_seg
FIRST¶
Wraps command run_first_all
Use FSL’s run_first_all command to segment subcortical volumes
http://www.fmrib.ox.ac.uk/fsl/first/index.html
Examples¶
>>> from nipype.interfaces import fsl
>>> first = fsl.FIRST()
>>> first.inputs.in_file = 'structural.nii'
>>> first.inputs.out_file = 'segmented.nii'
>>> res = first.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input data file
flag: -i %s, position: -2
out_file: (a file name, nipype default value: segmented)
output data file
flag: -o %s, position: -1
[Optional]
affine_file: (an existing file name)
Affine matrix to use (e.g. img2std.mat) (does not re-run
registration)
flag: -a %s, position: 6
args: (a string)
Additional parameters to the command
flag: %s
brain_extracted: (a boolean)
Input structural image is already brain-extracted
flag: -b, position: 2
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
list_of_specific_structures: (a list of at least 1 items which are a
string)
Runs only on the specified structures (e.g. L_Hipp, R_HippL_Accu,
R_Accu, L_Amyg, R_AmygL_Caud, R_Caud, L_Pall, R_PallL_Puta, R_Puta,
L_Thal, R_Thal, BrStem
flag: -s %s, position: 5
method: ('auto' or 'fast' or 'none', nipype default value: auto)
Method must be one of auto, fast, none, or it can be entered using
the 'method_as_numerical_threshold' input
flag: -m %s, position: 4
mutually_exclusive: method_as_numerical_threshold
method_as_numerical_threshold: (a float)
Specify a numerical threshold value or use the 'method' input to
choose auto, fast, or none
flag: -m %.4f, position: 4
no_cleanup: (a boolean)
Input structural image is already brain-extracted
flag: -d, position: 3
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
terminal_output: ('stream' or 'allatonce' or 'file' or '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
verbose: (a boolean)
Use verbose logging.
flag: -v, position: 1
Outputs:
bvars: (a list of items which are an existing file name)
bvars for each subcortical region
original_segmentations: (an existing file name)
3D image file containing the segmented regions as integer values.
Uses CMA labelling
segmentation_file: (an existing file name)
4D image file containing a single volume per segmented region
vtk_surfaces: (a list of items which are an existing file name)
VTK format meshes for each subcortical region
FLIRT¶
Wraps command flirt
Use FSL FLIRT for coregistration.
For complete details, see the FLIRT Documentation.
- To print out the command line help, use:
- fsl.FLIRT().inputs_help()
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> flt = fsl.FLIRT(bins=640, cost_func='mutualinfo')
>>> flt.inputs.in_file = 'structural.nii'
>>> flt.inputs.reference = 'mni.nii'
>>> flt.inputs.output_type = "NIFTI_GZ"
>>> flt.cmdline
'flirt -in structural.nii -ref mni.nii -out structural_flirt.nii.gz -omat structural_flirt.mat -bins 640 -searchcost mutualinfo'
>>> res = flt.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input file
flag: -in %s, position: 0
reference: (an existing file name)
reference file
flag: -ref %s, position: 1
[Optional]
angle_rep: ('quaternion' or 'euler')
representation of rotation angles
flag: -anglerep %s
apply_isoxfm: (a float)
as applyxfm but forces isotropic resampling
flag: -applyisoxfm %f
mutually_exclusive: apply_xfm
apply_xfm: (a boolean)
apply transformation supplied by in_matrix_file
flag: -applyxfm
requires: in_matrix_file
args: (a string)
Additional parameters to the command
flag: %s
bbrslope: (a float)
value of bbr slope
flag: -bbrslope %f
bbrtype: ('signed' or 'global_abs' or 'local_abs')
type of bbr cost function: signed [default], global_abs, local_abs
flag: -bbrtype %s
bgvalue: (a float)
use specified background value for points outside FOV
flag: -setbackground %f
bins: (an integer (int or long))
number of histogram bins
flag: -bins %d
coarse_search: (an integer (int or long))
coarse search delta angle
flag: -coarsesearch %d
cost: ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or
'leastsq' or 'labeldiff' or 'bbr')
cost function
flag: -cost %s
cost_func: ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or
'leastsq' or 'labeldiff' or 'bbr')
cost function
flag: -searchcost %s
datatype: ('char' or 'short' or 'int' or 'float' or 'double')
force output data type
flag: -datatype %s
display_init: (a boolean)
display initial matrix
flag: -displayinit
dof: (an integer (int or long))
number of transform degrees of freedom
flag: -dof %d
echospacing: (a float)
value of EPI echo spacing - units of seconds
flag: -echospacing %f
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
fieldmap: (a file name)
fieldmap image in rads/s - must be already registered to the
reference image
flag: -fieldmap %s
fieldmapmask: (a file name)
mask for fieldmap image
flag: -fieldmapmask %s
fine_search: (an integer (int or long))
fine search delta angle
flag: -finesearch %d
force_scaling: (a boolean)
force rescaling even for low-res images
flag: -forcescaling
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
in_matrix_file: (a file name)
input 4x4 affine matrix
flag: -init %s
in_weight: (an existing file name)
File for input weighting volume
flag: -inweight %s
interp: ('trilinear' or 'nearestneighbour' or 'sinc' or 'spline')
final interpolation method used in reslicing
flag: -interp %s
min_sampling: (a float)
set minimum voxel dimension for sampling
flag: -minsampling %f
no_clamp: (a boolean)
do not use intensity clamping
flag: -noclamp
no_resample: (a boolean)
do not change input sampling
flag: -noresample
no_resample_blur: (a boolean)
do not use blurring on downsampling
flag: -noresampblur
no_search: (a boolean)
set all angular searches to ranges 0 to 0
flag: -nosearch
out_file: (a file name)
registered output file
flag: -out %s, position: 2
out_log: (a file name)
output log
requires: save_log
out_matrix_file: (a file name)
output affine matrix in 4x4 asciii format
flag: -omat %s, position: 3
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
padding_size: (an integer (int or long))
for applyxfm: interpolates outside image by size
flag: -paddingsize %d
pedir: (an integer (int or long))
phase encode direction of EPI - 1/2/3=x/y/z & -1/-2/-3=-x/-y/-z
flag: -pedir %d
ref_weight: (an existing file name)
File for reference weighting volume
flag: -refweight %s
rigid2D: (a boolean)
use 2D rigid body mode - ignores dof
flag: -2D
save_log: (a boolean)
save to log file
schedule: (an existing file name)
replaces default schedule
flag: -schedule %s
searchr_x: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along x-axis, in degrees
flag: -searchrx %s
searchr_y: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along y-axis, in degrees
flag: -searchry %s
searchr_z: (a list of from 2 to 2 items which are an integer (int or
long))
search angles along z-axis, in degrees
flag: -searchrz %s
sinc_width: (an integer (int or long))
full-width in voxels
flag: -sincwidth %d
sinc_window: ('rectangular' or 'hanning' or 'blackman')
sinc window
flag: -sincwindow %s
terminal_output: ('stream' or 'allatonce' or 'file' or '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
uses_qform: (a boolean)
initialize using sform or qform
flag: -usesqform
verbose: (an integer (int or long))
verbose mode, 0 is least
flag: -verbose %d
wm_seg: (a file name)
white matter segmentation volume needed by BBR cost function
flag: -wmseg %s
wmcoords: (a file name)
white matter boundary coordinates for BBR cost function
flag: -wmcoords %s
wmnorms: (a file name)
white matter boundary normals for BBR cost function
flag: -wmnorms %s
Outputs:
out_file: (an existing file name)
path/name of registered file (if generated)
out_log: (a file name)
path/name of output log (if generated)
out_matrix_file: (an existing file name)
path/name of calculated affine transform (if generated)
FNIRT¶
Wraps command fnirt
Use FSL FNIRT for non-linear registration.
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> fnt = fsl.FNIRT(affine_file=example_data('trans.mat'))
>>> res = fnt.run(ref_file=example_data('mni.nii', in_file=example_data('structural.nii'))
T1 -> Mni153
>>> from nipype.interfaces import fsl
>>> fnirt_mprage = fsl.FNIRT()
>>> fnirt_mprage.inputs.in_fwhm = [8, 4, 2, 2]
>>> fnirt_mprage.inputs.subsampling_scheme = [4, 2, 1, 1]
Specify the resolution of the warps
>>> fnirt_mprage.inputs.warp_resolution = (6, 6, 6)
>>> res = fnirt_mprage.run(in_file='structural.nii', ref_file='mni.nii', warped_file='warped.nii', fieldcoeff_file='fieldcoeff.nii')
We can check the command line and confirm that it’s what we expect.
>>> fnirt_mprage.cmdline
'fnirt --cout=fieldcoeff.nii --in=structural.nii --infwhm=8,4,2,2 --ref=mni.nii --subsamp=4,2,1,1 --warpres=6,6,6 --iout=warped.nii'
Inputs:
[Mandatory]
in_file: (an existing file name)
name of input image
flag: --in=%s
ref_file: (an existing file name)
name of reference image
flag: --ref=%s
[Optional]
affine_file: (an existing file name)
name of file containing affine transform
flag: --aff=%s
apply_inmask: (a list of items which are 0 or 1)
list of iterations to use input mask on (1 to use, 0 to skip)
flag: --applyinmask=%s
mutually_exclusive: skip_inmask
apply_intensity_mapping: (a list of items which are 0 or 1)
List of subsampling levels to apply intensity mapping for (0 to
skip, 1 to apply)
flag: --estint=%s
mutually_exclusive: skip_intensity_mapping
apply_refmask: (a list of items which are 0 or 1)
list of iterations to use reference mask on (1 to use, 0 to skip)
flag: --applyrefmask=%s
mutually_exclusive: skip_refmask
args: (a string)
Additional parameters to the command
flag: %s
bias_regularization_lambda: (a float)
Weight of regularisation for bias-field, default 10000
flag: --biaslambda=%f
biasfield_resolution: (a tuple of the form: (an integer (int or
long), an integer (int or long), an integer (int or long)))
Resolution (in mm) of bias-field modelling local intensities,
default 50, 50, 50
flag: --biasres=%d,%d,%d
config_file: ('T1_2_MNI152_2mm' or 'FA_2_FMRIB58_1mm' or an existing
file name)
Name of config file specifying command line arguments
flag: --config=%s
derive_from_ref: (a boolean)
If true, ref image is used to calculate derivatives. Default false
flag: --refderiv
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
field_file: (a boolean or a file name)
name of output file with field or true
flag: --fout=%s
fieldcoeff_file: (a boolean or a file name)
name of output file with field coefficients or true
flag: --cout=%s
hessian_precision: ('double' or 'float')
Precision for representing Hessian, double or float. Default double
flag: --numprec=%s
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
in_fwhm: (a list of items which are an integer (int or long))
FWHM (in mm) of gaussian smoothing kernel for input volume, default
[6, 4, 2, 2]
flag: --infwhm=%s
in_intensitymap_file: (an existing file name)
name of file/files containing initial intensity mapingusually
generated by previos fnirt run
flag: --intin=%s
inmask_file: (an existing file name)
name of file with mask in input image space
flag: --inmask=%s
inmask_val: (a float)
Value to mask out in --in image. Default =0.0
flag: --impinval=%f
intensity_mapping_model: ('none' or 'global_linear' or
'global_non_linearlocal_linear' or 'global_non_linear_with_bias' or
'local_non_linear')
Model for intensity-mapping
flag: --intmod=%s
intensity_mapping_order: (an integer (int or long))
Order of poynomial for mapping intensities, default 5
flag: --intorder=%d
inwarp_file: (an existing file name)
name of file containing initial non-linear warps
flag: --inwarp=%s
jacobian_file: (a boolean or a file name)
name of file for writing out the Jacobianof the field (for
diagnostic or VBM purposes)
flag: --jout=%s
jacobian_range: (a tuple of the form: (a float, a float))
Allowed range of Jacobian determinants, default 0.01, 100.0
flag: --jacrange=%f,%f
log_file: (a file name)
Name of log-file
flag: --logout=%s
max_nonlin_iter: (a list of items which are an integer (int or long))
Max # of non-linear iterations list, default [5, 5, 5, 5]
flag: --miter=%s
modulatedref_file: (a boolean or a file name)
name of file for writing out intensity modulated--ref (for
diagnostic purposes)
flag: --refout=%s
out_intensitymap_file: (a boolean or a file name)
name of files for writing information pertaining to intensity
mapping
flag: --intout=%s
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
ref_fwhm: (a list of items which are an integer (int or long))
FWHM (in mm) of gaussian smoothing kernel for ref volume, default
[4, 2, 0, 0]
flag: --reffwhm=%s
refmask_file: (an existing file name)
name of file with mask in reference space
flag: --refmask=%s
refmask_val: (a float)
Value to mask out in --ref image. Default =0.0
flag: --imprefval=%f
regularization_lambda: (a list of items which are a float)
Weight of regularisation, default depending on --ssqlambda and
--regmod switches. See user documetation.
flag: --lambda=%s
regularization_model: ('membrane_energy' or 'bending_energy')
Model for regularisation of warp-field [membrane_energy
bending_energy], default bending_energy
flag: --regmod=%s
skip_implicit_in_masking: (a boolean)
skip implicit masking based on valuein --in image. Default = 0
flag: --impinm=0
skip_implicit_ref_masking: (a boolean)
skip implicit masking based on valuein --ref image. Default = 0
flag: --imprefm=0
skip_inmask: (a boolean)
skip specified inmask if set, default false
flag: --applyinmask=0
mutually_exclusive: apply_inmask
skip_intensity_mapping: (a boolean)
Skip estimate intensity-mapping default false
flag: --estint=0
mutually_exclusive: apply_intensity_mapping
skip_lambda_ssq: (a boolean)
If true, lambda is not weighted by current ssq, default false
flag: --ssqlambda=0
skip_refmask: (a boolean)
Skip specified refmask if set, default false
flag: --applyrefmask=0
mutually_exclusive: apply_refmask
spline_order: (an integer (int or long))
Order of spline, 2->Qadratic spline, 3->Cubic spline. Default=3
flag: --splineorder=%d
subsampling_scheme: (a list of items which are an integer (int or
long))
sub-sampling scheme, list, default [4, 2, 1, 1]
flag: --subsamp=%s
terminal_output: ('stream' or 'allatonce' or 'file' or '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
warp_resolution: (a tuple of the form: (an integer (int or long), an
integer (int or long), an integer (int or long)))
(approximate) resolution (in mm) of warp basis in x-, y- and
z-direction, default 10, 10, 10
flag: --warpres=%d,%d,%d
warped_file: (a file name)
name of output image
flag: --iout=%s
Outputs:
field_file: (a file name)
file with warp field
fieldcoeff_file: (an existing file name)
file with field coefficients
jacobian_file: (a file name)
file containing Jacobian of the field
log_file: (a file name)
Name of log-file
modulatedref_file: (a file name)
file containing intensity modulated --ref
out_intensitymap_file: (a file name)
file containing info pertaining to intensity mapping
warped_file: (an existing file name)
warped image
FUGUE¶
Wraps command fugue
FUGUE is, most generally, a set of tools for EPI distortion correction.
- Distortions may be corrected for
- improving registration with non-distorted images (e.g. structurals), or
- dealing with motion-dependent changes.
FUGUE is designed to deal only with the first case - improving registration.
Examples¶
Unwarping an input image (shift map is known)
>>> from nipype.interfaces.fsl.preprocess import FUGUE
>>> fugue = FUGUE()
>>> fugue.inputs.in_file = 'epi.nii'
>>> fugue.inputs.mask_file = 'epi_mask.nii'
>>> fugue.inputs.shift_in_file = 'vsm.nii' # Previously computed with fugue as well
>>> fugue.inputs.unwarp_direction = 'y'
>>> fugue.inputs.output_type = "NIFTI_GZ"
>>> fugue.cmdline
'fugue --in=epi.nii --mask=epi_mask.nii --loadshift=vsm.nii --unwarpdir=y --unwarp=epi_unwarped.nii.gz'
>>> fugue.run()
Warping an input image (shift map is known)
>>> from nipype.interfaces.fsl.preprocess import FUGUE
>>> fugue = FUGUE()
>>> fugue.inputs.in_file = 'epi.nii'
>>> fugue.inputs.forward_warping = True
>>> fugue.inputs.mask_file = 'epi_mask.nii'
>>> fugue.inputs.shift_in_file = 'vsm.nii' # Previously computed with fugue as well
>>> fugue.inputs.unwarp_direction = 'y'
>>> fugue.inputs.output_type = "NIFTI_GZ"
>>> fugue.cmdline
'fugue --in=epi.nii --mask=epi_mask.nii --loadshift=vsm.nii --unwarpdir=y --warp=epi_warped.nii.gz'
>>> fugue.run()
Computing the vsm (unwrapped phase map is known)
>>> from nipype.interfaces.fsl.preprocess import FUGUE
>>> fugue = FUGUE()
>>> fugue.inputs.phasemap_in_file = 'epi_phasediff.nii'
>>> fugue.inputs.mask_file = 'epi_mask.nii'
>>> fugue.inputs.dwell_to_asym_ratio = (0.77e-3 * 3) / 2.46e-3
>>> fugue.inputs.unwarp_direction = 'y'
>>> fugue.inputs.save_shift = True
>>> fugue.inputs.output_type = "NIFTI_GZ"
>>> fugue.cmdline
'fugue --dwelltoasym=0.9390243902 --mask=epi_mask.nii --phasemap=epi_phasediff.nii --saveshift=epi_phasediff_vsm.nii.gz --unwarpdir=y'
>>> fugue.run()
Inputs:
[Mandatory]
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
asym_se_time: (a float)
set the fieldmap asymmetric spin echo time (sec)
flag: --asym=%.10f
despike_2dfilter: (a boolean)
apply a 2D de-spiking filter
flag: --despike
despike_threshold: (a float)
specify the threshold for de-spiking (default=3.0)
flag: --despikethreshold=%s
dwell_time: (a float)
set the EPI dwell time per phase-encode line - same as echo spacing
- (sec)
flag: --dwell=%.10f
dwell_to_asym_ratio: (a float)
set the dwell to asym time ratio
flag: --dwelltoasym=%.10f
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
fmap_in_file: (an existing file name)
filename for loading fieldmap (rad/s)
flag: --loadfmap=%s
fmap_out_file: (a file name)
filename for saving fieldmap (rad/s)
flag: --savefmap=%s
forward_warping: (a boolean, nipype default value: False)
apply forward warping instead of unwarping
fourier_order: (an integer (int or long))
apply Fourier (sinusoidal) fitting of order N
flag: --fourier=%d
icorr: (a boolean)
apply intensity correction to unwarping (pixel shift method only)
flag: --icorr
requires: shift_in_file
icorr_only: (a boolean)
apply intensity correction only
flag: --icorronly
requires: unwarped_file
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
in_file: (an existing file name)
filename of input volume
flag: --in=%s
mask_file: (an existing file name)
filename for loading valid mask
flag: --mask=%s
median_2dfilter: (a boolean)
apply 2D median filtering
flag: --median
no_extend: (a boolean)
do not apply rigid-body extrapolation to the fieldmap
flag: --noextend
no_gap_fill: (a boolean)
do not apply gap-filling measure to the fieldmap
flag: --nofill
nokspace: (a boolean)
do not use k-space forward warping
flag: --nokspace
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
pava: (a boolean)
apply monotonic enforcement via PAVA
flag: --pava
phase_conjugate: (a boolean)
apply phase conjugate method of unwarping
flag: --phaseconj
phasemap_in_file: (an existing file name)
filename for input phase image
flag: --phasemap=%s
poly_order: (an integer (int or long))
apply polynomial fitting of order N
flag: --poly=%d
save_fmap: (a boolean)
write field map volume
mutually_exclusive: save_unmasked_fmap
save_shift: (a boolean)
write pixel shift volume
mutually_exclusive: save_unmasked_shift
save_unmasked_fmap: (a boolean)
saves the unmasked fieldmap when using --savefmap
flag: --unmaskfmap
mutually_exclusive: save_fmap
save_unmasked_shift: (a boolean)
saves the unmasked shiftmap when using --saveshift
flag: --unmaskshift
mutually_exclusive: save_shift
shift_in_file: (an existing file name)
filename for reading pixel shift volume
flag: --loadshift=%s
shift_out_file: (a file name)
filename for saving pixel shift volume
flag: --saveshift=%s
smooth2d: (a float)
apply 2D Gaussian smoothing of sigma N (in mm)
flag: --smooth2=%.2f
smooth3d: (a float)
apply 3D Gaussian smoothing of sigma N (in mm)
flag: --smooth3=%.2f
terminal_output: ('stream' or 'allatonce' or 'file' or '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
unwarp_direction: ('x' or 'y' or 'z' or 'x-' or 'y-' or 'z-')
specifies direction of warping (default y)
flag: --unwarpdir=%s
unwarped_file: (a file name)
apply unwarping and save as filename
flag: --unwarp=%s
mutually_exclusive: warped_file
requires: in_file
warped_file: (a file name)
apply forward warping and save as filename
flag: --warp=%s
mutually_exclusive: unwarped_file
requires: in_file
Outputs:
fmap_out_file: (a file name)
fieldmap file
shift_out_file: (a file name)
voxel shift map file
unwarped_file: (a file name)
unwarped file
warped_file: (a file name)
forward warped file
MCFLIRT¶
Wraps command mcflirt
Use FSL MCFLIRT to do within-modality motion correction.
For complete details, see the MCFLIRT Documentation.
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> mcflt = fsl.MCFLIRT(in_file=example_data('functional.nii'), cost='mutualinfo')
>>> res = mcflt.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
timeseries to motion-correct
flag: -in %s, position: 0
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
bins: (an integer (int or long))
number of histogram bins
flag: -bins %d
cost: ('mutualinfo' or 'woods' or 'corratio' or 'normcorr' or
'normmi' or 'leastsquares')
cost function to optimize
flag: -cost %s
dof: (an integer (int or long))
degrees of freedom for the transformation
flag: -dof %d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
init: (an existing file name)
inital transformation matrix
flag: -init %s
interpolation: ('spline' or 'nn' or 'sinc')
interpolation method for transformation
flag: -%s_final
mean_vol: (a boolean)
register to mean volume
flag: -meanvol
out_file: (a file name)
file to write
flag: -out %s
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
ref_file: (an existing file name)
target image for motion correction
flag: -reffile %s
ref_vol: (an integer (int or long))
volume to align frames to
flag: -refvol %d
rotation: (an integer (int or long))
scaling factor for rotation tolerances
flag: -rotation %d
save_mats: (a boolean)
save transformation matrices
flag: -mats
save_plots: (a boolean)
save transformation parameters
flag: -plots
save_rms: (a boolean)
save rms displacement parameters
flag: -rmsabs -rmsrel
scaling: (a float)
scaling factor to use
flag: -scaling %.2f
smooth: (a float)
smoothing factor for the cost function
flag: -smooth %.2f
stages: (an integer (int or long))
stages (if 4, perform final search with sinc interpolation
flag: -stages %d
stats_imgs: (a boolean)
produce variance and std. dev. images
flag: -stats
terminal_output: ('stream' or 'allatonce' or 'file' or '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
use_contour: (a boolean)
run search on contour images
flag: -edge
use_gradient: (a boolean)
run search on gradient images
flag: -gdt
Outputs:
mat_file: (a list of items which are an existing file name)
transformation matrices
mean_img: (an existing file name)
mean timeseries image
out_file: (an existing file name)
motion-corrected timeseries
par_file: (an existing file name)
text-file with motion parameters
rms_files: (a list of items which are an existing file name)
absolute and relative displacement parameters
std_img: (an existing file name)
standard deviation image
variance_img: (an existing file name)
variance image
PRELUDE¶
Wraps command prelude
Use FSL prelude to do phase unwrapping
Examples¶
Please insert examples for use of this command
Inputs:
[Mandatory]
complex_phase_file: (an existing file name)
complex phase input volume
flag: --complex=%s
mutually_exclusive: magnitude_file, phase_file
magnitude_file: (an existing file name)
file containing magnitude image
flag: --abs=%s
mutually_exclusive: complex_phase_file
phase_file: (an existing file name)
raw phase file
flag: --phase=%s
mutually_exclusive: complex_phase_file
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
end: (an integer (int or long))
final image number to process (default Inf)
flag: --end=%d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
label_file: (a file name)
saving the area labels output
flag: --labels=%s
labelprocess2d: (a boolean)
does label processing in 2D (slice at a time)
flag: --labelslices
mask_file: (an existing file name)
filename of mask input volume
flag: --mask=%s
num_partitions: (an integer (int or long))
number of phase partitions to use
flag: --numphasesplit=%d
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
process2d: (a boolean)
does all processing in 2D (slice at a time)
flag: --slices
mutually_exclusive: labelprocess2d
process3d: (a boolean)
forces all processing to be full 3D
flag: --force3D
mutually_exclusive: labelprocess2d, process2d
rawphase_file: (a file name)
saving the raw phase output
flag: --rawphase=%s
removeramps: (a boolean)
remove phase ramps during unwrapping
flag: --removeramps
savemask_file: (a file name)
saving the mask volume
flag: --savemask=%s
start: (an integer (int or long))
first image number to process (default 0)
flag: --start=%d
terminal_output: ('stream' or 'allatonce' or 'file' or '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
threshold: (a float)
intensity threshold for masking
flag: --thresh=%.10f
unwrapped_phase_file: (a file name)
file containing unwrapepd phase
flag: --unwrap=%s
Outputs:
unwrapped_phase_file: (an existing file name)
unwrapped phase file
SUSAN¶
Wraps command susan
use FSL SUSAN to perform smoothing
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> anatfile
anatomical.nii
>>> sus = fsl.SUSAN()
>>> sus.inputs.in_file = example_data('structural.nii')
>>> sus.inputs.brightness_threshold = 2000.0
>>> sus.inputs.fwhm = 8.0
>>> result = sus.run()
Inputs:
[Mandatory]
brightness_threshold: (a float)
brightness threshold and should be greater than noise level and less
than contrast of edges to be preserved.
flag: %.10f, position: 2
fwhm: (a float)
fwhm of smoothing, in mm, gets converted using sqrt(8*log(2))
flag: %.10f, position: 3
in_file: (an existing file name)
filename of input timeseries
flag: %s, position: 1
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
dimension: (3 or 2, nipype default value: 3)
within-plane (2) or fully 3D (3)
flag: %d, position: 4
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
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 file name
flag: %s, position: -1
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
terminal_output: ('stream' or 'allatonce' or 'file' or '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
usans: (a list of at most 2 items which are a tuple of the form: (an
existing file name, a float), nipype default value: [])
determines whether the smoothing area (USAN) is to be found from
secondary images (0, 1 or 2). A negative value for any brightness
threshold will auto-set the threshold at 10% of the robust range
use_median: (1 or 0, nipype default value: 1)
whether to use a local median filter in the cases where single-point
noise is detected
flag: %d, position: 5
Outputs:
smoothed_file: (an existing file name)
smoothed output file
SliceTimer¶
Wraps command slicetimer
use FSL slicetimer to perform slice timing correction.
Examples¶
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> st = fsl.SliceTimer()
>>> st.inputs.in_file = example_data('functional.nii')
>>> st.inputs.interleaved = True
>>> result = st.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
filename of input timeseries
flag: --in=%s, position: 0
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
custom_order: (an existing file name)
filename of single-column custom interleave order file (first slice
is referred to as 1 not 0)
flag: --ocustom=%s
custom_timings: (an existing file name)
slice timings, in fractions of TR, range 0:1 (default is 0.5 = no
shift)
flag: --tcustom=%s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
global_shift: (a float)
shift in fraction of TR, range 0:1 (default is 0.5 = no shift)
flag: --tglobal
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
index_dir: (a boolean)
slice indexing from top to bottom
flag: --down
interleaved: (a boolean)
use interleaved acquisition
flag: --odd
out_file: (a file name)
filename of output timeseries
flag: --out=%s
output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
slice_direction: (1 or 2 or 3)
direction of slice acquisition (x=1, y=2, z=3) - default is z
flag: --direction=%d
terminal_output: ('stream' or 'allatonce' or 'file' or '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
time_repetition: (a float)
Specify TR of data - default is 3s
flag: --repeat=%f
Outputs:
slice_time_corrected_file: (an existing file name)
slice time corrected file