interfaces.fsl.epi¶
ApplyTOPUP¶
Wraps the executable command applytopup
.
Interface for FSL topup, a tool for estimating and correcting susceptibility induced distortions. General reference and use example.
Examples¶
>>> from nipype.interfaces.fsl import ApplyTOPUP
>>> applytopup = ApplyTOPUP()
>>> applytopup.inputs.in_files = ["epi.nii", "epi_rev.nii"]
>>> applytopup.inputs.encoding_file = "topup_encoding.txt"
>>> applytopup.inputs.in_topup_fieldcoef = "topup_fieldcoef.nii.gz"
>>> applytopup.inputs.in_topup_movpar = "topup_movpar.txt"
>>> applytopup.inputs.output_type = "NIFTI_GZ"
>>> applytopup.cmdline
'applytopup --datain=topup_encoding.txt --imain=epi.nii,epi_rev.nii --inindex=1,2 --topup=topup --out=epi_corrected.nii.gz'
>>> res = applytopup.run()
Inputs:
[Mandatory]
in_files: (a list of items which are an existing file name)
name of file with images
argument: ``--imain=%s``
encoding_file: (an existing file name)
name of text file with PE directions/times
argument: ``--datain=%s``
[Optional]
out_corrected: (a file name)
output (warped) image
argument: ``--out=%s``
datatype: (u'char' or u'short' or u'int' or u'float' or u'double')
force output data type
argument: ``-d=%s``
in_index: (a list of items which are an integer (int or long))
comma separated list of indices corresponding to --datain
argument: ``--inindex=%s``
in_topup_fieldcoef: (an existing file name)
topup file containing the field coefficients
argument: ``--topup=%s``
requires: in_topup_movpar
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
interp: (u'trilinear' or u'spline')
interpolation method
argument: ``--interp=%s``
method: (u'jac' or u'lsr')
use jacobian modulation (jac) or least-squares resampling (lsr)
argument: ``--method=%s``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
in_topup_movpar: (an existing file name)
topup movpar.txt file
requires: in_topup_fieldcoef
Outputs:
out_corrected: (an existing file name)
name of 4D image file with unwarped images
References:¶
None
EPIDeWarp¶
Wraps the executable command epidewarp.fsl
.
Wraps the unwarping script epidewarp.fsl.
Warning
deprecated in FSL, please use
nipype.workflows.dmri.preprocess.epi.sdc_fmb()
instead.
Examples¶
>>> from nipype.interfaces.fsl import EPIDeWarp
>>> dewarp = EPIDeWarp()
>>> dewarp.inputs.epi_file = "functional.nii"
>>> dewarp.inputs.mag_file = "magnitude.nii"
>>> dewarp.inputs.dph_file = "phase.nii"
>>> dewarp.inputs.output_type = "NIFTI_GZ"
>>> dewarp.cmdline
'epidewarp.fsl --mag magnitude.nii --dph phase.nii --epi functional.nii --esp 0.58 --exfdw .../exfdw.nii.gz --nocleanup --sigma 2 --tediff 2.46 --tmpdir .../temp --vsm .../vsm.nii.gz'
>>> res = dewarp.run()
Inputs:
[Mandatory]
mag_file: (an existing file name)
Magnitude file
argument: ``--mag %s``, position: 0
dph_file: (an existing file name)
Phase file assumed to be scaled from 0 to 4095
argument: ``--dph %s``
[Optional]
exf_file: (an existing file name)
example func volume (or use epi)
argument: ``--exf %s``
esp: (a float, nipype default value: 0.58)
EPI echo spacing
argument: ``--esp %s``
nocleanup: (a boolean, nipype default value: True)
no cleanup
argument: ``--nocleanup``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
epi_file: (an existing file name)
EPI volume to unwarp
argument: ``--epi %s``
tmpdir: (a string)
tmpdir
argument: ``--tmpdir %s``
cleanup: (a boolean)
cleanup
argument: ``--cleanup``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
exfdw: (a string)
dewarped example func volume
argument: ``--exfdw %s``
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
epidw: (a string)
dewarped epi volume
argument: ``--epidw %s``
sigma: (an integer (int or long), nipype default value: 2)
2D spatial gaussing smoothing stdev (default = 2mm)
argument: ``--sigma %s``
vsm: (a string)
voxel shift map
argument: ``--vsm %s``
tediff: (a float, nipype default value: 2.46)
difference in B0 field map TEs
argument: ``--tediff %s``
Outputs:
unwarped_file: (a file name)
unwarped epi file
vsm_file: (a file name)
voxel shift map
exfdw: (a file name)
dewarped functional volume example
exf_mask: (a file name)
Mask from example functional volume
References:¶
None
Eddy¶
Wraps the executable command eddy_openmp
.
Interface for FSL eddy, a tool for estimating and correcting eddy currents induced distortions. User guide and more info regarding acqp file.
Examples¶
>>> from nipype.interfaces.fsl import Eddy
>>> eddy = Eddy()
>>> eddy.inputs.in_file = 'epi.nii'
>>> eddy.inputs.in_mask = 'epi_mask.nii'
>>> eddy.inputs.in_index = 'epi_index.txt'
>>> eddy.inputs.in_acqp = 'epi_acqp.txt'
>>> eddy.inputs.in_bvec = 'bvecs.scheme'
>>> eddy.inputs.in_bval = 'bvals.scheme'
>>> eddy.inputs.use_cuda = True
>>> eddy.cmdline
'eddy_cuda --ff=10.0 --acqp=epi_acqp.txt --bvals=bvals.scheme --bvecs=bvecs.scheme --imain=epi.nii --index=epi_index.txt --mask=epi_mask.nii --niter=5 --nvoxhp=1000 --out=.../eddy_corrected'
>>> eddy.inputs.use_cuda = False
>>> eddy.cmdline
'eddy_openmp --ff=10.0 --acqp=epi_acqp.txt --bvals=bvals.scheme --bvecs=bvecs.scheme --imain=epi.nii --index=epi_index.txt --mask=epi_mask.nii --niter=5 --nvoxhp=1000 --out=.../eddy_corrected'
>>> res = eddy.run()
Inputs:
[Mandatory]
in_acqp: (an existing file name)
File containing acquisition parameters
argument: ``--acqp=%s``
in_index: (an existing file name)
File containing indices for all volumes in --imain into --acqp and
--topup
argument: ``--index=%s``
in_mask: (an existing file name)
Mask to indicate brain
argument: ``--mask=%s``
in_file: (an existing file name)
File containing all the images to estimate distortions for
argument: ``--imain=%s``
in_bval: (an existing file name)
File containing the b-values for all volumes in --imain
argument: ``--bvals=%s``
in_bvec: (an existing file name)
File containing the b-vectors for all volumes in --imain
argument: ``--bvecs=%s``
[Optional]
out_base: (a unicode string, nipype default value: eddy_corrected)
basename for output (warped) image
argument: ``--out=%s``
session: (an existing file name)
File containing session indices for all volumes in --imain
argument: ``--session=%s``
repol: (a boolean)
Detect and replace outlier slices
argument: ``--repol``
fwhm: (a float)
FWHM for conditioning filter when estimating the parameters
argument: ``--fwhm=%s``
in_topup_movpar: (an existing file name)
topup movpar.txt file
requires: in_topup_fieldcoef
field: (a unicode string)
NonTOPUP fieldmap scaled in Hz - filename has to be provided without
an extension. TOPUP is strongly recommended
argument: ``--field=%s``
fep: (a boolean)
Fill empty planes in x- or y-directions
argument: ``--fep``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
method: (u'jac' or u'lsr')
Final resampling method (jacobian/least squares)
argument: ``--resamp=%s``
fudge_factor: (a float, nipype default value: 10.0)
Fudge factor for hyperparameter error variance
argument: ``--ff=%s``
is_shelled: (a boolean)
Override internal check to ensure that date are acquired on a set of
b-value shells
argument: ``--data_is_shelled``
niter: (an integer (int or long), nipype default value: 5)
Number of iterations
argument: ``--niter=%s``
interp: (u'spline' or u'trilinear')
Interpolation model for estimation step
argument: ``--interp=%s``
in_topup_fieldcoef: (an existing file name)
topup file containing the field coefficients
argument: ``--topup=%s``
requires: in_topup_movpar
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
nvoxhp: (an integer (int or long), nipype default value: 1000)
# of voxels used to estimate the hyperparameters
argument: ``--nvoxhp=%s``
dont_peas: (a boolean)
Do NOT perform a post-eddy alignment of shells
argument: ``--dont_peas``
field_mat: (an existing file name)
Matrix that specifies the relative locations of the field specified
by --field and first volume in file --imain
argument: ``--field_mat=%s``
num_threads: (an integer (int or long), nipype default value: 1)
Number of openmp threads to use
dont_sep_offs_move: (a boolean)
Do NOT attempt to separate field offset from subject movement
argument: ``--dont_sep_offs_move``
use_cuda: (a boolean)
Run eddy using cuda gpu
slm: (u'none' or u'linear' or u'quadratic')
Second level EC model
argument: ``--slm=%s``
cnr_maps: (a boolean)
Output CNR-Maps
argument: ``--cnr_maps``
flm: (u'linear' or u'quadratic' or u'cubic')
First level EC model
argument: ``--flm=%s``
residuals: (a boolean)
Output Residuals
argument: ``--residuals``
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
Outputs:
out_corrected: (an existing file name)
4D image file containing all the corrected volumes
out_parameter: (an existing file name)
text file with parameters definining the field andmovement for each
scan
out_cnr_maps: (an existing file name)
path/name of file with the cnr_maps
out_residuals: (an existing file name)
path/name of file with the residuals
out_shell_alignment_parameters: (an existing file name)
File containing rigid body movement parameters between the different
shells as estimated by a post-hoc mutual information based
registration
out_movement_rms: (an existing file name)
Summary of the "total movement" in each volume
out_outlier_report: (an existing file name)
Text-file with a plain language report on what outlier slices eddy
has found
out_restricted_movement_rms: (an existing file name)
Summary of the "total movement" in each volume disregarding
translation in the PE direction
out_rotated_bvecs: (an existing file name)
File containing rotated b-values for all volumes
References:¶
None
EddyCorrect¶
Wraps the executable command eddy_correct
.
Warning
Deprecated in FSL. Please use
nipype.interfaces.fsl.epi.Eddy
instead
Example¶
>>> from nipype.interfaces.fsl import EddyCorrect
>>> eddyc = EddyCorrect(in_file='diffusion.nii',
... out_file="diffusion_edc.nii", ref_num=0)
>>> eddyc.cmdline
'eddy_correct diffusion.nii diffusion_edc.nii 0'
Inputs:
[Mandatory]
ref_num: (an integer (int or long), nipype default value: 0)
reference number
argument: ``%d``, position: 2
in_file: (an existing file name)
4D input file
argument: ``%s``, position: 0
[Optional]
out_file: (a file name)
4D output file
argument: ``%s``, position: 1
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
Outputs:
eddy_corrected: (an existing file name)
path/name of 4D eddy corrected output file
References:¶
None
EpiReg¶
Wraps the executable command epi_reg
.
Runs FSL epi_reg script for simultaneous coregistration and fieldmap unwarping.
Examples¶
>>> from nipype.interfaces.fsl import EpiReg
>>> epireg = EpiReg()
>>> epireg.inputs.epi='epi.nii'
>>> epireg.inputs.t1_head='T1.nii'
>>> epireg.inputs.t1_brain='T1_brain.nii'
>>> epireg.inputs.out_base='epi2struct'
>>> epireg.inputs.fmap='fieldmap_phase_fslprepared.nii'
>>> epireg.inputs.fmapmag='fieldmap_mag.nii'
>>> epireg.inputs.fmapmagbrain='fieldmap_mag_brain.nii'
>>> epireg.inputs.echospacing=0.00067
>>> epireg.inputs.pedir='y'
>>> epireg.cmdline
'epi_reg --echospacing=0.000670 --fmap=fieldmap_phase_fslprepared.nii --fmapmag=fieldmap_mag.nii --fmapmagbrain=fieldmap_mag_brain.nii --noclean --pedir=y --epi=epi.nii --t1=T1.nii --t1brain=T1_brain.nii --out=epi2struct'
>>> epireg.run()
Inputs:
[Mandatory]
t1_head: (an existing file name)
wholehead T1 image
argument: ``--t1=%s``, position: -3
t1_brain: (an existing file name)
brain extracted T1 image
argument: ``--t1brain=%s``, position: -2
epi: (an existing file name)
EPI image
argument: ``--epi=%s``, position: -4
[Optional]
fmap: (an existing file name)
fieldmap image (in rad/s)
argument: ``--fmap=%s``
no_fmapreg: (a boolean)
do not perform registration of fmap to T1 (use if fmap already
registered)
argument: ``--nofmapreg``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
fmapmag: (an existing file name)
fieldmap magnitude image - wholehead
argument: ``--fmapmag=%s``
no_clean: (a boolean, nipype default value: True)
do not clean up intermediate files
argument: ``--noclean``
out_base: (a string, nipype default value: epi2struct)
output base name
argument: ``--out=%s``, position: -1
wmseg: (an existing file name)
white matter segmentation of T1 image, has to be named like the
t1brain and end on _wmseg
argument: ``--wmseg=%s``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
weight_image: (an existing file name)
weighting image (in T1 space)
argument: ``--weight=%s``
pedir: (u'x' or u'y' or u'z' or u'-x' or u'-y' or u'-z')
phase encoding direction, dir = x/y/z/-x/-y/-z
argument: ``--pedir=%s``
echospacing: (a float)
Effective EPI echo spacing (sometimes called dwell time) - in
seconds
argument: ``--echospacing=%f``
fmapmagbrain: (an existing file name)
fieldmap magnitude image - brain extracted
argument: ``--fmapmagbrain=%s``
Outputs:
fmap_str: (an existing file name)
fieldmap in structural space
out_file: (an existing file name)
unwarped and coregistered epi input
fmap_epi: (an existing file name)
fieldmap in epi space
wmseg: (an existing file name)
white matter segmentation used in flirt bbr
fullwarp: (an existing file name)
warpfield to unwarp epi and transform into structural space
seg: (an existing file name)
white matter, gray matter, csf segmentation
out_1vol: (an existing file name)
unwarped and coregistered single volume
shiftmap: (an existing file name)
shiftmap in epi space
wmedge: (an existing file name)
white matter edges for visualization
fmap2str_mat: (an existing file name)
rigid fieldmap-to-structural transform
epi2str_inv: (an existing file name)
rigid structural-to-epi transform
fmapmag_str: (an existing file name)
fieldmap magnitude image in structural space
epi2str_mat: (an existing file name)
rigid epi-to-structural transform
fmap2epi_mat: (an existing file name)
rigid fieldmap-to-epi transform
References:¶
None
PrepareFieldmap¶
Wraps the executable command fsl_prepare_fieldmap
.
Interface for the fsl_prepare_fieldmap script (FSL 5.0)
Prepares a fieldmap suitable for FEAT from SIEMENS data - saves output in
rad/s format (e.g. `fsl_prepare_fieldmap SIEMENS
images_3_gre_field_mapping images_4_gre_field_mapping fmap_rads 2.65`
).
Examples¶
>>> from nipype.interfaces.fsl import PrepareFieldmap
>>> prepare = PrepareFieldmap()
>>> prepare.inputs.in_phase = "phase.nii"
>>> prepare.inputs.in_magnitude = "magnitude.nii"
>>> prepare.inputs.output_type = "NIFTI_GZ"
>>> prepare.cmdline
'fsl_prepare_fieldmap SIEMENS phase.nii magnitude.nii .../phase_fslprepared.nii.gz 2.460000'
>>> res = prepare.run()
Inputs:
[Mandatory]
delta_TE: (a float, nipype default value: 2.46)
echo time difference of the fieldmap sequence in ms. (usually 2.46ms
in Siemens)
argument: ``%f``, position: -2
in_phase: (an existing file name)
Phase difference map, in SIEMENS format range from 0-4096 or 0-8192)
argument: ``%s``, position: 2
in_magnitude: (an existing file name)
Magnitude difference map, brain extracted
argument: ``%s``, position: 3
[Optional]
out_fieldmap: (a file name)
output name for prepared fieldmap
argument: ``%s``, position: 4
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
nocheck: (a boolean, nipype default value: False)
do not perform sanity checks for image size/range/dimensions
argument: ``--nocheck``, position: -1
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
scanner: (a string, nipype default value: SIEMENS)
must be SIEMENS
argument: ``%s``, position: 1
Outputs:
out_fieldmap: (an existing file name)
output name for prepared fieldmap
References:¶
None
SigLoss¶
Wraps the executable command sigloss
.
Estimates signal loss from a field map (in rad/s)
Examples¶
>>> from nipype.interfaces.fsl import SigLoss
>>> sigloss = SigLoss()
>>> sigloss.inputs.in_file = "phase.nii"
>>> sigloss.inputs.echo_time = 0.03
>>> sigloss.inputs.output_type = "NIFTI_GZ"
>>> sigloss.cmdline
'sigloss --te=0.030000 -i phase.nii -s .../phase_sigloss.nii.gz'
>>> res = sigloss.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
b0 fieldmap file
argument: ``-i %s``
[Optional]
echo_time: (a float)
echo time in seconds
argument: ``--te=%f``
out_file: (a file name)
output signal loss estimate file
argument: ``-s %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
slice_direction: (u'x' or u'y' or u'z')
slicing direction
argument: ``-d %s``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
mask_file: (an existing file name)
brain mask file
argument: ``-m %s``
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
Outputs:
out_file: (an existing file name)
signal loss estimate file
References:¶
None
TOPUP¶
Wraps the executable command topup
.
Interface for FSL topup, a tool for estimating and correcting susceptibility induced distortions. See FSL documentation for reference, usage examples, and exemplary config files.
Examples¶
>>> from nipype.interfaces.fsl import TOPUP
>>> topup = TOPUP()
>>> topup.inputs.in_file = "b0_b0rev.nii"
>>> topup.inputs.encoding_file = "topup_encoding.txt"
>>> topup.inputs.output_type = "NIFTI_GZ"
>>> topup.cmdline
'topup --config=b02b0.cnf --datain=topup_encoding.txt --imain=b0_b0rev.nii --out=b0_b0rev_base --iout=b0_b0rev_corrected.nii.gz --fout=b0_b0rev_field.nii.gz --jacout=jac --logout=b0_b0rev_topup.log --rbmout=xfm --dfout=warpfield'
>>> res = topup.run()
Inputs:
[Mandatory]
readout_times: (a list of items which are a float)
readout times (dwell times by # phase-encode steps minus 1)
mutually_exclusive: encoding_file
requires: encoding_direction
encoding_direction: (a list of items which are u'y' or u'x' or u'z'
or u'x-' or u'y-' or u'z-')
encoding direction for automatic generation of encoding_file
argument: ``--datain=%s``
mutually_exclusive: encoding_file
requires: readout_times
in_file: (an existing file name)
name of 4D file with images
argument: ``--imain=%s``
encoding_file: (an existing file name)
name of text file with PE directions/times
argument: ``--datain=%s``
mutually_exclusive: encoding_direction
[Optional]
minmet: (0 or 1)
Minimisation method 0=Levenberg-Marquardt, 1=Scaled Conjugate
Gradient
argument: ``--minmet=%d``
splineorder: (an integer (int or long))
order of spline, 2->Qadratic spline, 3->Cubic spline
argument: ``--splineorder=%d``
out_base: (a file name)
base-name of output files (spline coefficients (Hz) and movement
parameters)
argument: ``--out=%s``
out_mat_prefix: (a unicode string, nipype default value: xfm)
prefix for the realignment matrices
argument: ``--rbmout=%s``
subsamp: (an integer (int or long))
sub-sampling scheme
argument: ``--subsamp=%d``
regmod: (u'bending_energy' or u'membrane_energy')
Regularisation term implementation. Defaults to bending_energy. Note
that the two functions have vastly different scales. The membrane
energy is based on the first derivatives and the bending energy on
the second derivatives. The second derivatives will typically be
much smaller than the first derivatives, so input lambda will have
to be larger for bending_energy to yield approximately the same
level of regularisation.
argument: ``--regmod=%s``
out_logfile: (a file name)
name of log-file
argument: ``--logout=%s``
scale: (0 or 1)
If set (=1), the images are individually scaled to a common mean
argument: ``--scale=%d``
fwhm: (a float)
FWHM (in mm) of gaussian smoothing kernel
argument: ``--fwhm=%f``
out_jac_prefix: (a unicode string, nipype default value: jac)
prefix for the warpfield images
argument: ``--jacout=%s``
out_field: (a file name)
name of image file with field (Hz)
argument: ``--fout=%s``
regrid: (1 or 0)
If set (=1), the calculations are done in a different grid
argument: ``--regrid=%d``
config: (a string, nipype default value: b02b0.cnf)
Name of config file specifying command line arguments
argument: ``--config=%s``
out_corrected: (a file name)
name of 4D image file with unwarped images
argument: ``--iout=%s``
max_iter: (an integer (int or long))
max # of non-linear iterations
argument: ``--miter=%d``
interp: (u'spline' or u'linear')
Image interpolation model, linear or spline.
argument: ``--interp=%s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
warp_res: (a float)
(approximate) resolution (in mm) of warp basis for the different
sub-sampling levels
argument: ``--warpres=%f``
estmov: (1 or 0)
estimate movements if set
argument: ``--estmov=%d``
ssqlambda: (1 or 0)
Weight lambda by the current value of the ssd. If used (=1), the
effective weight of regularisation term becomes higher for the
initial iterations, therefore initial steps are a little smoother
than they would without weighting. This reduces the risk of finding
a local minimum.
argument: ``--ssqlambda=%d``
reg_lambda: (a float)
Weight of regularisation, default depending on --ssqlambda and
--regmod switches.
argument: ``--lambda=%0.f``
environ: (a dictionary with keys which are a newbytes or None or a
newstr or None and with values which are a newbytes or None or a
newstr or None, nipype default value: {})
Environment variables
output_type: (u'NIFTI_PAIR' or u'NIFTI_PAIR_GZ' or u'NIFTI_GZ' or
u'NIFTI')
FSL output type
numprec: (u'double' or u'float')
Precision for representing Hessian, double or float.
argument: ``--numprec=%s``
out_warp_prefix: (a unicode string, nipype default value: warpfield)
prefix for the warpfield images (in mm)
argument: ``--dfout=%s``
Outputs:
out_corrected: (a file name)
name of 4D image file with unwarped images
out_movpar: (an existing file name)
movpar.txt output file
out_mats: (a list of items which are an existing file name)
realignment matrices
out_fieldcoef: (an existing file name)
file containing the field coefficients
out_logfile: (a file name)
name of log-file
out_enc_file: (a file name)
encoding directions file output for applytopup
out_field: (a file name)
name of image file with field (Hz)
out_jacs: (a list of items which are an existing file name)
Jacobian images
out_warps: (a list of items which are an existing file name)
warpfield images
References:¶
None