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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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
References:: None
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.preprocess.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 or uses_qform to use
the affine matrix stored in the reference header
flag: -applyxfm
args: (a unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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)
References:: None
BET¶
Wraps command bet
Use FSL BET command for skull stripping.
For complete details, see the BET Documentation.
Examples¶
>>> from nipype.interfaces import fsl
>>> btr = fsl.BET()
>>> btr.inputs.in_file = 'structural.nii'
>>> btr.inputs.frac = 0.7
>>> btr.inputs.out_file = 'brain_anat.nii'
>>> btr.cmdline
'bet structural.nii brain_anat.nii -f 0.70'
>>> res = btr.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input file to skull strip
flag: %s, position: 0
[Optional]
args: (a unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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)
References:: None
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
>>> fastr = fsl.FAST()
>>> fastr.inputs.in_files = 'structural.nii'
>>> fastr.inputs.out_basename = 'fast_'
>>> fastr.cmdline
'fast -o fast_ -S 1 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 unicode string)
Additional parameters to the command
flag: %s
bias_iters: (1 <= a long integer <= 10)
number of main-loop iterations during bias-field removal
flag: -I %d
bias_lowpass: (4 <= a long integer <= 40)
bias field smoothing extent (FWHM) in mm
flag: -l %d
environ: (a dictionary with keys which are a bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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 <= a long 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 <= a long 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_GZ' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
'NIFTI')
FSL output type
probability_maps: (a boolean)
outputs individual probability maps
flag: -p
segment_iters: (1 <= a long 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
References:: None
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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
unicode 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_GZ' or 'NIFTI_PAIR' 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
References:: None
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 or uses_qform to use
the affine matrix stored in the reference header
flag: -applyxfm
args: (a unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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)
References:: None
FNIRT¶
Wraps command fnirt
Use FSL FNIRT for non-linear registration.
For complete details, see the FNIRT Documentation.
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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: (a list of from 1 to 2 items which are an
existing file name)
name of file/files containing initial intensity mapping usually
generated by previous 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 Jacobian of 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_GZ' or 'NIFTI_PAIR' 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 value in --in image. Default = 0
flag: --impinm=0
skip_implicit_ref_masking: (a boolean)
skip implicit masking based on value in --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 list of from 2 to 2 items which are a file
name)
files containing info pertaining to intensity mapping
warped_file: (an existing file name)
warped image
References:: None
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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
References:: None
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
>>> mcflt = fsl.MCFLIRT()
>>> mcflt.inputs.in_file = 'functional.nii'
>>> mcflt.inputs.cost = 'mutualinfo'
>>> mcflt.inputs.out_file = 'moco.nii'
>>> mcflt.cmdline
'mcflirt -in functional.nii -cost mutualinfo -out moco.nii'
>>> res = mcflt.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
timeseries to motion-correct
flag: -in %s, position: 0
[Optional]
args: (a unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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 (if mean_vol=True)
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
References:: None
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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
References:: None
SUSAN¶
Wraps command susan
use FSL SUSAN to perform smoothing
For complete details, see the SUSAN Documentation.
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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
References:: None
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 unicode 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 bytes or None or a value
of class 'str' and with values which are a bytes or None or a value
of class '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_GZ' or 'NIFTI_PAIR' 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
References:: None