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]
in_topup_fieldcoef: (an existing file name)
topup file containing the field coefficients
argument: ``--topup=%s``
requires: in_topup_movpar
in_topup_movpar: (an existing file name)
topup movpar.txt file
requires: in_topup_fieldcoef
interp: ('trilinear' or 'spline')
interpolation method
argument: ``--interp=%s``
out_corrected: (a file name)
output (warped) image
argument: ``--out=%s``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
datatype: ('char' or 'short' or 'int' or 'float' or 'double')
force output data type
argument: ``-d=%s``
method: ('jac' or 'lsr')
use jacobian modulation (jac) or least-squares resampling (lsr)
argument: ``--method=%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``
args: (a unicode string)
Additional parameters to the command
argument: ``%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
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]
nocleanup: (a boolean, nipype default value: True)
no cleanup
argument: ``--nocleanup``
vsm: (a string)
voxel shift map
argument: ``--vsm %s``
cleanup: (a boolean)
cleanup
argument: ``--cleanup``
esp: (a float, nipype default value: 0.58)
EPI echo spacing
argument: ``--esp %s``
epidw: (a string)
dewarped epi volume
argument: ``--epidw %s``
exf_file: (an existing file name)
example func volume (or use epi)
argument: ``--exf %s``
sigma: (an integer (int or long), nipype default value: 2)
2D spatial gaussing smoothing stdev (default = 2mm)
argument: ``--sigma %s``
epi_file: (an existing file name)
EPI volume to unwarp
argument: ``--epi %s``
tediff: (a float, nipype default value: 2.46)
difference in B0 field map TEs
argument: ``--tediff %s``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
tmpdir: (a string)
tmpdir
argument: ``--tmpdir %s``
exfdw: (a string)
dewarped example func volume
argument: ``--exfdw %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%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
Outputs:
vsm_file: (a file name)
voxel shift map
unwarped_file: (a file name)
unwarped epi file
exf_mask: (a file name)
Mask from example functional volume
exfdw: (a file name)
dewarped functional volume example
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_file: (an existing file name)
File containing all the images to estimate distortions for
argument: ``--imain=%s``
in_bvec: (an existing file name)
File containing the b-vectors for all volumes in --imain
argument: ``--bvecs=%s``
in_index: (an existing file name)
File containing indices for all volumes in --imain into --acqp and
--topup
argument: ``--index=%s``
in_acqp: (an existing file name)
File containing acquisition parameters
argument: ``--acqp=%s``
in_bval: (an existing file name)
File containing the b-values for all volumes in --imain
argument: ``--bvals=%s``
in_mask: (an existing file name)
Mask to indicate brain
argument: ``--mask=%s``
[Optional]
out_base: (a unicode string, nipype default value: eddy_corrected)
basename for output (warped) image
argument: ``--out=%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``
slm: ('none' or 'linear' or 'quadratic')
Second level EC model
argument: ``--slm=%s``
niter: (an integer (int or long), nipype default value: 5)
Number of iterations
argument: ``--niter=%s``
dont_peas: (a boolean)
Do NOT perform a post-eddy alignment of shells
argument: ``--dont_peas``
residuals: (a boolean)
Output Residuals
argument: ``--residuals``
session: (an existing file name)
File containing session indices for all volumes in --imain
argument: ``--session=%s``
fudge_factor: (a float, nipype default value: 10.0)
Fudge factor for hyperparameter error variance
argument: ``--ff=%s``
use_cuda: (a boolean)
Run eddy using cuda gpu
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
fep: (a boolean)
Fill empty planes in x- or y-directions
argument: ``--fep``
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``
flm: ('linear' or 'quadratic' or 'cubic')
First level EC model
argument: ``--flm=%s``
nvoxhp: (an integer (int or long), nipype default value: 1000)
# of voxels used to estimate the hyperparameters
argument: ``--nvoxhp=%s``
cnr_maps: (a boolean)
Output CNR-Maps
argument: ``--cnr_maps``
in_topup_fieldcoef: (an existing file name)
topup file containing the field coefficients
argument: ``--topup=%s``
requires: in_topup_movpar
fwhm: (a float)
FWHM for conditioning filter when estimating the parameters
argument: ``--fwhm=%s``
field: (a unicode string)
NonTOPUP fieldmap scaled in Hz - filename has to be provided without
an extension. TOPUP is strongly recommended
argument: ``--field=%s``
in_topup_movpar: (an existing file name)
topup movpar.txt file
requires: in_topup_fieldcoef
interp: ('spline' or 'trilinear')
Interpolation model for estimation step
argument: ``--interp=%s``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
dont_sep_offs_move: (a boolean)
Do NOT attempt to separate field offset from subject movement
argument: ``--dont_sep_offs_move``
num_threads: (an integer (int or long), nipype default value: 1)
Number of openmp threads to use
repol: (a boolean)
Detect and replace outlier slices
argument: ``--repol``
method: ('jac' or 'lsr')
Final resampling method (jacobian/least squares)
argument: ``--resamp=%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
Outputs:
out_cnr_maps: (an existing file name)
path/name of file with the cnr_maps
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_residuals: (an existing file name)
path/name of file with the residuals
out_movement_rms: (an existing file name)
Summary of the "total movement" in each volume
out_parameter: (an existing file name)
text file with parameters definining the field andmovement for each
scan
out_corrected: (an existing file name)
4D image file containing all the corrected volumes
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
out_outlier_report: (an existing file name)
Text-file with a plain language report on what outlier slices eddy
has found
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]
in_file: (an existing file name)
4D input file
argument: ``%s``, position: 0
ref_num: (an integer (int or long), nipype default value: 0)
reference number
argument: ``%d``, position: 2
[Optional]
out_file: (a file name)
4D output file
argument: ``%s``, position: 1
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
args: (a unicode string)
Additional parameters to the command
argument: ``%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
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]
epi: (an existing file name)
EPI image
argument: ``--epi=%s``, position: -4
t1_brain: (an existing file name)
brain extracted T1 image
argument: ``--t1brain=%s``, position: -2
t1_head: (an existing file name)
wholehead T1 image
argument: ``--t1=%s``, position: -3
[Optional]
out_base: (a string, nipype default value: epi2struct)
output base name
argument: ``--out=%s``, position: -1
fmapmagbrain: (an existing file name)
fieldmap magnitude image - brain extracted
argument: ``--fmapmagbrain=%s``
no_clean: (a boolean, nipype default value: True)
do not clean up intermediate files
argument: ``--noclean``
no_fmapreg: (a boolean)
do not perform registration of fmap to T1 (use if fmap already
registered)
argument: ``--nofmapreg``
pedir: ('x' or 'y' or 'z' or '-x' or '-y' or '-z')
phase encoding direction, dir = x/y/z/-x/-y/-z
argument: ``--pedir=%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
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``
fmap: (an existing file name)
fieldmap image (in rad/s)
argument: ``--fmap=%s``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
fmapmag: (an existing file name)
fieldmap magnitude image - wholehead
argument: ``--fmapmag=%s``
weight_image: (an existing file name)
weighting image (in T1 space)
argument: ``--weight=%s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
echospacing: (a float)
Effective EPI echo spacing (sometimes called dwell time) - in
seconds
argument: ``--echospacing=%f``
Outputs:
fullwarp: (an existing file name)
warpfield to unwarp epi and transform into structural space
out_file: (an existing file name)
unwarped and coregistered epi input
epi2str_inv: (an existing file name)
rigid structural-to-epi transform
fmap2str_mat: (an existing file name)
rigid fieldmap-to-structural transform
fmap_str: (an existing file name)
fieldmap in structural space
out_1vol: (an existing file name)
unwarped and coregistered single volume
epi2str_mat: (an existing file name)
rigid epi-to-structural transform
fmap2epi_mat: (an existing file name)
rigid fieldmap-to-epi transform
fmapmag_str: (an existing file name)
fieldmap magnitude image in structural space
shiftmap: (an existing file name)
shiftmap in epi space
wmseg: (an existing file name)
white matter segmentation used in flirt bbr
wmedge: (an existing file name)
white matter edges for visualization
seg: (an existing file name)
white matter, gray matter, csf segmentation
fmap_epi: (an existing file name)
fieldmap in epi space
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_magnitude: (an existing file name)
Magnitude difference map, brain extracted
argument: ``%s``, position: 3
in_phase: (an existing file name)
Phase difference map, in SIEMENS format range from 0-4096 or 0-8192)
argument: ``%s``, position: 2
[Optional]
out_fieldmap: (a file name)
output name for prepared fieldmap
argument: ``%s``, position: 4
scanner: (a string, nipype default value: SIEMENS)
must be SIEMENS
argument: ``%s``, position: 1
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
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 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
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
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``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
mask_file: (an existing file name)
brain mask file
argument: ``-m %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
slice_direction: ('x' or 'y' or 'z')
slicing direction
argument: ``-d %s``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
out_file: (a file name)
output signal loss estimate file
argument: ``-s %s``
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]
in_file: (an existing file name)
name of 4D file with images
argument: ``--imain=%s``
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_file: (an existing file name)
name of text file with PE directions/times
argument: ``--datain=%s``
mutually_exclusive: encoding_direction
encoding_direction: (a list of items which are 'y' or 'x' or 'z' or
'x-' or 'y-' or 'z-')
encoding direction for automatic generation of encoding_file
argument: ``--datain=%s``
mutually_exclusive: encoding_file
requires: readout_times
[Optional]
out_base: (a file name)
base-name of output files (spline coefficients (Hz) and movement
parameters)
argument: ``--out=%s``
out_logfile: (a file name)
name of log-file
argument: ``--logout=%s``
estmov: (1 or 0)
estimate movements if set
argument: ``--estmov=%d``
config: (a string, nipype default value: b02b0.cnf)
Name of config file specifying command line arguments
argument: ``--config=%s``
regmod: ('bending_energy' or '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``
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``
out_mat_prefix: (a unicode string, nipype default value: xfm)
prefix for the realignment matrices
argument: ``--rbmout=%s``
out_corrected: (a file name)
name of 4D image file with unwarped images
argument: ``--iout=%s``
subsamp: (an integer (int or long))
sub-sampling scheme
argument: ``--subsamp=%d``
regrid: (1 or 0)
If set (=1), the calculations are done in a different grid
argument: ``--regrid=%d``
max_iter: (an integer (int or long))
max # of non-linear iterations
argument: ``--miter=%d``
reg_lambda: (a float)
Weight of regularisation, default depending on --ssqlambda and
--regmod switches.
argument: ``--lambda=%0.f``
out_jac_prefix: (a unicode string, nipype default value: jac)
prefix for the warpfield images
argument: ``--jacout=%s``
out_warp_prefix: (a unicode string, nipype default value: warpfield)
prefix for the warpfield images (in mm)
argument: ``--dfout=%s``
numprec: ('double' or 'float')
Precision for representing Hessian, double or float.
argument: ``--numprec=%s``
out_field: (a file name)
name of image file with field (Hz)
argument: ``--fout=%s``
fwhm: (a float)
FWHM (in mm) of gaussian smoothing kernel
argument: ``--fwhm=%f``
interp: ('spline' or 'linear')
Image interpolation model, linear or spline.
argument: ``--interp=%s``
splineorder: (an integer (int or long))
order of spline, 2->Qadratic spline, 3->Cubic spline
argument: ``--splineorder=%d``
args: (a unicode string)
Additional parameters to the command
argument: ``%s``
output_type: ('NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI' or
'NIFTI_PAIR')
FSL output type
warp_res: (a float)
(approximate) resolution (in mm) of warp basis for the different
sub-sampling levels
argument: ``--warpres=%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
minmet: (0 or 1)
Minimisation method 0=Levenberg-Marquardt, 1=Scaled Conjugate
Gradient
argument: ``--minmet=%d``
scale: (0 or 1)
If set (=1), the images are individually scaled to a common mean
argument: ``--scale=%d``
Outputs:
out_warps: (a list of items which are an existing file name)
warpfield images
out_fieldcoef: (an existing file name)
file containing the field coefficients
out_corrected: (a file name)
name of 4D image file with unwarped images
out_movpar: (an existing file name)
movpar.txt output file
out_logfile: (a file name)
name of log-file
out_jacs: (a list of items which are an existing file name)
Jacobian images
out_mats: (a list of items which are an existing file name)
realignment matrices
out_field: (a file name)
name of image file with field (Hz)
out_enc_file: (a file name)
encoding directions file output for applytopup
References:¶
None