interfaces.freesurfer.utils¶
AddXFormToHeader¶
Wraps command mri_add_xform_to_header
Just adds specified xform to the volume header
(!) WARNING: transform input MUST be an absolute path to a DataSink’ed transform or the output will reference a transform in the workflow cache directory!
>>> from nipype.interfaces.freesurfer import AddXFormToHeader
>>> adder = AddXFormToHeader()
>>> adder.inputs.in_file = 'norm.mgz'
>>> adder.inputs.transform = 'trans.mat'
>>> adder.cmdline
'mri_add_xform_to_header trans.mat norm.mgz output.mgz'
>>> adder.inputs.copy_name = True
>>> adder.cmdline
'mri_add_xform_to_header -c trans.mat norm.mgz output.mgz'
>>> adder.run()
References:¶
[https://surfer.nmr.mgh.harvard.edu/fswiki/mri_add_xform_to_header]
Inputs:
[Mandatory]
in_file: (an existing file name)
input volume
flag: %s, position: -2
transform: (a file name)
xfm file
flag: %s, position: -3
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
copy_name: (a boolean)
do not try to load the xfmfile, just copy name
flag: -c
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
out_file: (a file name, nipype default value: output.mgz)
output volume
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
verbose: (a boolean)
be verbose
flag: -v
Outputs:
out_file: (an existing file name)
output volume
Aparc2Aseg¶
Wraps command mri_aparc2aseg
Maps the cortical labels from the automatic cortical parcellation (aparc) to the automatic segmentation volume (aseg). The result can be used as the aseg would. The algorithm is to find each aseg voxel labeled as cortex (3 and 42) and assign it the label of the closest cortical vertex. If the voxel is not in the ribbon (as defined by mri/ lh.ribbon and rh.ribbon), then the voxel is marked as unknown (0). This can be turned off with –noribbon. The cortical parcellation is obtained from subject/label/hemi.aparc.annot which should be based on the curvature.buckner40.filled.desikan_killiany.gcs atlas. The aseg is obtained from subject/mri/aseg.mgz and should be based on the RB40_talairach_2005-07-20.gca atlas. If these atlases are used, then the segmentations can be viewed with tkmedit and the FreeSurferColorLUT.txt color table found in $FREESURFER_HOME. These are the default atlases used by recon-all.
Examples¶
>>> from nipype.interfaces.freesurfer import Aparc2Aseg
>>> aparc2aseg = Aparc2Aseg()
>>> aparc2aseg.inputs.lh_white = 'lh.pial'
>>> aparc2aseg.inputs.rh_white = 'lh.pial'
>>> aparc2aseg.inputs.lh_pial = 'lh.pial'
>>> aparc2aseg.inputs.rh_pial = 'lh.pial'
>>> aparc2aseg.inputs.lh_ribbon = 'label.mgz'
>>> aparc2aseg.inputs.rh_ribbon = 'label.mgz'
>>> aparc2aseg.inputs.ribbon = 'label.mgz'
>>> aparc2aseg.inputs.lh_annotation = 'lh.pial'
>>> aparc2aseg.inputs.rh_annotation = 'lh.pial'
>>> aparc2aseg.inputs.out_file = 'aparc+aseg.mgz'
>>> aparc2aseg.inputs.label_wm = True
>>> aparc2aseg.inputs.rip_unknown = True
>>> aparc2aseg.cmdline
'mri_aparc2aseg --labelwm --o aparc+aseg.mgz --rip-unknown --s subject_id'
Inputs:
[Mandatory]
lh_annotation: (an existing file name)
Input file must be <subject_id>/label/lh.aparc.annot
lh_pial: (an existing file name)
Input file must be <subject_id>/surf/lh.pial
lh_ribbon: (an existing file name)
Input file must be <subject_id>/mri/lh.ribbon.mgz
lh_white: (an existing file name)
Input file must be <subject_id>/surf/lh.white
out_file: (a file name)
Full path of file to save the output segmentation in
flag: --o %s
rh_annotation: (an existing file name)
Input file must be <subject_id>/label/rh.aparc.annot
rh_pial: (an existing file name)
Input file must be <subject_id>/surf/rh.pial
rh_ribbon: (an existing file name)
Input file must be <subject_id>/mri/rh.ribbon.mgz
rh_white: (an existing file name)
Input file must be <subject_id>/surf/rh.white
ribbon: (an existing file name)
Input file must be <subject_id>/mri/ribbon.mgz
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: --s %s
[Optional]
a2009s: (a boolean)
Using the a2009s atlas
flag: --a2009s
args: (a unicode string)
Additional parameters to the command
flag: %s
aseg: (an existing file name)
Input aseg file
flag: --aseg %s
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the input
files to the node directory.
ctxseg: (an existing file name)
flag: --ctxseg %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
filled: (an existing file name)
Implicit input filled file. Only required with FS v5.3.
hypo_wm: (a boolean)
Label hypointensities as WM
flag: --hypo-as-wm
label_wm: (a boolean)
For each voxel labeled as white matter in the aseg, re-assign
its label to be that of the closest cortical point if its
distance is less than dmaxctx
flag: --labelwm
rip_unknown: (a boolean)
Do not label WM based on 'unknown' corical label
flag: --rip-unknown
subjects_dir: (an existing directory name)
subjects directory
volmask: (a boolean)
Volume mask flag
flag: --volmask
Outputs:
out_file: (a file name)
Output aseg file
flag: %s
Apas2Aseg¶
Wraps command apas2aseg
Converts aparc+aseg.mgz into something like aseg.mgz by replacing the cortical segmentations 1000-1035 with 3 and 2000-2035 with 42. The advantage of this output is that the cortical label conforms to the actual surface (this is not the case with aseg.mgz).
Examples¶
>>> from nipype.interfaces.freesurfer import Apas2Aseg
>>> apas2aseg = Apas2Aseg()
>>> apas2aseg.inputs.in_file = 'aseg.mgz'
>>> apas2aseg.inputs.out_file = 'output.mgz'
>>> apas2aseg.cmdline
'apas2aseg --i aseg.mgz --o output.mgz'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input aparc+aseg.mgz
flag: --i %s
out_file: (a file name)
Output aseg file
flag: --o %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output aseg file
flag: %s
ApplyMask¶
Wraps command mri_mask
Use Freesurfer’s mri_mask to apply a mask to an image.
The mask file need not be binarized; it can be thresholded above a given value before application. It can also optionally be transformed into input space with an LTA matrix.
Inputs:
[Mandatory]
in_file: (an existing file name)
input image (will be masked)
flag: %s, position: -3
mask_file: (an existing file name)
image defining mask space
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
invert_xfm: (a boolean)
invert transformation
flag: -invert
keep_mask_deletion_edits: (a boolean)
transfer voxel-deletion edits (voxels=1) from mask to out vol
flag: -keep_mask_deletion_edits
mask_thresh: (a float)
threshold mask before applying
flag: -T %.4f
out_file: (a file name)
final image to write
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
transfer: (an integer (int or long))
transfer only voxel value # from mask to out
flag: -transfer %d
use_abs: (a boolean)
take absolute value of mask before applying
flag: -abs
xfm_file: (an existing file name)
LTA-format transformation matrix to align mask with input
flag: -xform %s
xfm_source: (an existing file name)
image defining transform source space
flag: -lta_src %s
xfm_target: (an existing file name)
image defining transform target space
flag: -lta_dst %s
Outputs:
out_file: (an existing file name)
masked image
CheckTalairachAlignment¶
Wraps command talairach_afd
This program detects Talairach alignment failures
Examples¶
>>> from nipype.interfaces.freesurfer import CheckTalairachAlignment
>>> checker = CheckTalairachAlignment()
>>> checker.inputs.in_file = 'trans.mat'
>>> checker.inputs.threshold = 0.005
>>> checker.cmdline
'talairach_afd -T 0.005 -xfm trans.mat'
>>> checker.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
specify the talairach.xfm file to check
flag: -xfm %s, position: -1
mutually_exclusive: subject
subject: (a string)
specify subject's name
flag: -subj %s, position: -1
mutually_exclusive: in_file
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
subjects_dir: (an existing directory name)
subjects directory
threshold: (a float, nipype default value: 0.01)
Talairach transforms for subjects with p-values <= T are considered
as very unlikely default=0.010
flag: -T %.3f
Outputs:
out_file: (a file name)
The input file for CheckTalairachAlignment
Contrast¶
Wraps command pctsurfcon
Compute surface-wise gray/white contrast
Examples¶
>>> from nipype.interfaces.freesurfer import Contrast
>>> contrast = Contrast()
>>> contrast.inputs.subject_id = '10335'
>>> contrast.inputs.hemisphere = 'lh'
>>> contrast.inputs.white = 'lh.white'
>>> contrast.inputs.thickness = 'lh.thickness'
>>> contrast.inputs.annotation = '../label/lh.aparc.annot'
>>> contrast.inputs.cortex = '../label/lh.cortex.label'
>>> contrast.inputs.rawavg = '../mri/rawavg.mgz'
>>> contrast.inputs.orig = '../mri/orig.mgz'
>>> contrast.cmdline
'pctsurfcon --lh-only --s 10335'
Inputs:
[Mandatory]
annotation: (a file name)
Input annotation file must be
<subject_id>/label/<hemisphere>.aparc.annot
cortex: (a file name)
Input cortex label must be
<subject_id>/label/<hemisphere>.cortex.label
hemisphere: ('lh' or 'rh')
Hemisphere being processed
flag: --%s-only
orig: (an existing file name)
Implicit input file mri/orig.mgz
rawavg: (an existing file name)
Implicit input file mri/rawavg.mgz
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: --s %s
thickness: (an existing file name)
Input file must be <subject_id>/surf/?h.thickness
white: (an existing file name)
Input file must be <subject_id>/surf/<hemisphere>.white
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the input
files to the node directory.
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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_contrast: (a file name)
Output contrast file from Contrast
out_log: (an existing file name)
Output log from Contrast
out_stats: (a file name)
Output stats file from Contrast
Curvature¶
Wraps command mris_curvature
This program will compute the second fundamental form of a cortical surface. It will create two new files <hemi>.<surface>.H and <hemi>.<surface>.K with the mean and Gaussian curvature respectively.
Examples¶
>>> from nipype.interfaces.freesurfer import Curvature
>>> curv = Curvature()
>>> curv.inputs.in_file = 'lh.pial'
>>> curv.inputs.save = True
>>> curv.cmdline
'mris_curvature -w lh.pial'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for Curvature
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
averages: (an integer (int or long))
Perform this number iterative averages of curvature measure before
saving
flag: -a %d
copy_input: (a boolean)
Copy input file to current directory
distances: (a tuple of the form: (an integer (int or long), an
integer (int or long)))
Undocumented input integer distances
flag: -distances %d %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
n: (a boolean)
Undocumented boolean flag
flag: -n
save: (a boolean)
Save curvature files (will only generate screen output without this
option)
flag: -w
subjects_dir: (an existing directory name)
subjects directory
threshold: (a float)
Undocumented input threshold
flag: -thresh %.3f
Outputs:
out_gauss: (a file name)
Gaussian curvature output file
out_mean: (a file name)
Mean curvature output file
CurvatureStats¶
Wraps command mris_curvature_stats
In its simplest usage, ‘mris_curvature_stats’ will compute a set of statistics on its input <curvFile>. These statistics are the mean and standard deviation of the particular curvature on the surface, as well as the results from several surface-based integrals.
Additionally, ‘mris_curvature_stats’ can report the max/min curvature values, and compute a simple histogram based on all curvature values.
Curvatures can also be normalised and constrained to a given range before computation.
Principal curvature (K, H, k1 and k2) calculations on a surface structure can also be performed, as well as several functions derived from k1 and k2.
Finally, all output to the console, as well as any new curvatures that result from the above calculations can be saved to a series of text and binary-curvature files.
Examples¶
>>> from nipype.interfaces.freesurfer import CurvatureStats
>>> curvstats = CurvatureStats()
>>> curvstats.inputs.hemisphere = 'lh'
>>> curvstats.inputs.curvfile1 = 'lh.pial'
>>> curvstats.inputs.curvfile2 = 'lh.pial'
>>> curvstats.inputs.surface = 'lh.pial'
>>> curvstats.inputs.out_file = 'lh.curv.stats'
>>> curvstats.inputs.values = True
>>> curvstats.inputs.min_max = True
>>> curvstats.inputs.write = True
>>> curvstats.cmdline
'mris_curvature_stats -m -o lh.curv.stats -F pial -G --writeCurvatureFiles subject_id lh pial pial'
Inputs:
[Mandatory]
curvfile1: (an existing file name)
Input file for CurvatureStats
flag: %s, position: -2
curvfile2: (an existing file name)
Input file for CurvatureStats
flag: %s, position: -1
hemisphere: ('lh' or 'rh')
Hemisphere being processed
flag: %s, position: -3
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: %s, position: -4
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the input
files to the node directory.
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
min_max: (a boolean)
Output min / max information for the processed curvature.
flag: -m
out_file: (a file name)
Output curvature stats file
flag: -o %s
subjects_dir: (an existing directory name)
subjects directory
surface: (an existing file name)
Specify surface file for CurvatureStats
flag: -F %s
values: (a boolean)
Triggers a series of derived curvature values
flag: -G
write: (a boolean)
Write curvature files
flag: --writeCurvatureFiles
Outputs:
out_file: (a file name)
Output curvature stats file
EulerNumber¶
Wraps command mris_euler_number
This program computes EulerNumber for a cortical surface
Examples¶
>>> from nipype.interfaces.freesurfer import EulerNumber
>>> ft = EulerNumber()
>>> ft.inputs.in_file = 'lh.pial'
>>> ft.cmdline
'mris_euler_number lh.pial'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for EulerNumber
flag: %s, position: -1
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file for EulerNumber
ExtractMainComponent¶
Wraps command mris_extract_main_component
Extract the main component of a tesselated surface
Examples¶
>>> from nipype.interfaces.freesurfer import ExtractMainComponent
>>> mcmp = ExtractMainComponent(in_file='lh.pial')
>>> mcmp.cmdline
'mris_extract_main_component lh.pial lh.maincmp'
Inputs:
[Mandatory]
in_file: (an existing file name)
input surface file
flag: %s, position: 1
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
surface containing main component
flag: %s, position: 2
Outputs:
out_file: (an existing file name)
surface containing main component
FixTopology¶
Wraps command mris_fix_topology
This program computes a mapping from the unit sphere onto the surface of the cortex from a previously generated approximation of the cortical surface, thus guaranteeing a topologically correct surface.
Examples¶
>>> from nipype.interfaces.freesurfer import FixTopology
>>> ft = FixTopology()
>>> ft.inputs.in_orig = 'lh.orig'
>>> ft.inputs.in_inflated = 'lh.inflated'
>>> ft.inputs.sphere = 'lh.qsphere.nofix'
>>> ft.inputs.hemisphere = 'lh'
>>> ft.inputs.subject_id = '10335'
>>> ft.inputs.mgz = True
>>> ft.inputs.ga = True
>>> ft.cmdline
'mris_fix_topology -ga -mgz -sphere qsphere.nofix 10335 lh'
Inputs:
[Mandatory]
copy_inputs: (a boolean)
If running as a node, set this to True otherwise, the topology
fixing will be done in place.
hemisphere: (a string)
Hemisphere being processed
flag: %s, position: -1
in_brain: (an existing file name)
Implicit input brain.mgz
in_inflated: (an existing file name)
Undocumented input file <hemisphere>.inflated
in_orig: (an existing file name)
Undocumented input file <hemisphere>.orig
in_wm: (an existing file name)
Implicit input wm.mgz
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
ga: (a boolean)
No documentation. Direct questions to analysis-
bugs@nmr.mgh.harvard.edu
flag: -ga
mgz: (a boolean)
No documentation. Direct questions to analysis-
bugs@nmr.mgh.harvard.edu
flag: -mgz
seed: (an integer (int or long))
Seed for setting random number generator
flag: -seed %d
sphere: (a file name)
Sphere input file
flag: -sphere %s
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file for FixTopology
Jacobian¶
Wraps command mris_jacobian
This program computes the Jacobian of a surface mapping.
Examples¶
>>> from nipype.interfaces.freesurfer import Jacobian
>>> jacobian = Jacobian()
>>> jacobian.inputs.in_origsurf = 'lh.pial'
>>> jacobian.inputs.in_mappedsurf = 'lh.pial'
>>> jacobian.cmdline
'mris_jacobian lh.pial lh.pial lh.jacobian'
Inputs:
[Mandatory]
in_mappedsurf: (an existing file name)
Mapped surface
flag: %s, position: -2
in_origsurf: (an existing file name)
Original surface
flag: %s, position: -3
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
Output Jacobian of the surface mapping
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output Jacobian of the surface mapping
LTAConvert¶
Wraps command lta_convert
Convert different transformation formats. Some formats may require you to pass an image if the geometry information is missing form the transform file format.
For complete details, see the lta_convert documentation.
Inputs:
[Mandatory]
in_fsl: (an existing file name)
input transform of FSL type
flag: --infsl %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
in_itk: (an existing file name)
input transform of ITK type
flag: --initk %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
in_lta: (an existing file name or 'identity.nofile')
input transform of LTA type
flag: --inlta %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
in_mni: (an existing file name)
input transform of MNI/XFM type
flag: --inmni %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
in_niftyreg: (an existing file name)
input transform of Nifty Reg type (inverse RAS2RAS)
flag: --inniftyreg %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
in_reg: (an existing file name)
input transform of TK REG type (deprecated format)
flag: --inreg %s
mutually_exclusive: in_lta, in_fsl, in_mni, in_reg, in_niftyreg,
in_itk
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
invert: (a boolean)
flag: --invert
ltavox2vox: (a boolean)
flag: --ltavox2vox
requires: out_lta
out_fsl: (a boolean or a file name)
output transform in FSL format
flag: --outfsl %s
out_itk: (a boolean or a file name)
output transform in ITK format
flag: --outitk %s
out_lta: (a boolean or a file name)
output linear transform (LTA Freesurfer format)
flag: --outlta %s
out_mni: (a boolean or a file name)
output transform in MNI/XFM format
flag: --outmni %s
out_reg: (a boolean or a file name)
output transform in reg dat format
flag: --outreg %s
source_file: (an existing file name)
flag: --src %s
target_conform: (a boolean)
flag: --trgconform
target_file: (an existing file name)
flag: --trg %s
Outputs:
out_fsl: (an existing file name)
output transform in FSL format
out_itk: (an existing file name)
output transform in ITK format
out_lta: (an existing file name)
output linear transform (LTA Freesurfer format)
out_mni: (an existing file name)
output transform in MNI/XFM format
out_reg: (an existing file name)
output transform in reg dat format
MRIFill¶
Wraps command mri_fill
This program creates hemispheric cutting planes and fills white matter with specific values for subsequent surface tesselation.
Examples¶
>>> from nipype.interfaces.freesurfer import MRIFill
>>> fill = MRIFill()
>>> fill.inputs.in_file = 'wm.mgz'
>>> fill.inputs.out_file = 'filled.mgz'
>>> fill.cmdline
'mri_fill wm.mgz filled.mgz'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input white matter file
flag: %s, position: -2
out_file: (a file name)
Output filled volume file name for MRIFill
flag: %s, position: -1
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
log_file: (a file name)
Output log file for MRIFill
flag: -a %s
segmentation: (an existing file name)
Input segmentation file for MRIFill
flag: -segmentation %s
subjects_dir: (an existing directory name)
subjects directory
transform: (an existing file name)
Input transform file for MRIFill
flag: -xform %s
Outputs:
log_file: (a file name)
Output log file from MRIFill
out_file: (a file name)
Output file from MRIFill
MRIMarchingCubes¶
Wraps command mri_mc
Uses Freesurfer’s mri_mc to create surfaces by tessellating a given input volume
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> mc = fs.MRIMarchingCubes()
>>> mc.inputs.in_file = 'aseg.mgz'
>>> mc.inputs.label_value = 17
>>> mc.inputs.out_file = 'lh.hippocampus'
>>> mc.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
Input volume to tesselate voxels from.
flag: %s, position: 1
label_value: (an integer (int or long))
Label value which to tesselate from the input volume. (integer, if
input is "filled.mgz" volume, 127 is rh, 255 is lh)
flag: %d, position: 2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
connectivity_value: (an integer (int or long), nipype default value:
1)
Alter the marching cubes connectivity: 1=6+,2=18,3=6,4=26
(default=1)
flag: %d, 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
out_file: (a file name)
output filename or True to generate one
flag: ./%s, position: -2
subjects_dir: (an existing directory name)
subjects directory
Outputs:
surface: (an existing file name)
binary surface of the tessellation
MRIPretess¶
Wraps command mri_pretess
Uses Freesurfer’s mri_pretess to prepare volumes to be tessellated.
Description¶
Changes white matter (WM) segmentation so that the neighbors of all voxels labeled as WM have a face in common - no edges or corners allowed.
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> pretess = fs.MRIPretess()
>>> pretess.inputs.in_filled = 'wm.mgz'
>>> pretess.inputs.in_norm = 'norm.mgz'
>>> pretess.inputs.nocorners = True
>>> pretess.cmdline
'mri_pretess -nocorners wm.mgz wm norm.mgz wm_pretesswm.mgz'
>>> pretess.run()
Inputs:
[Mandatory]
in_filled: (an existing file name)
filled volume, usually wm.mgz
flag: %s, position: -4
in_norm: (an existing file name)
the normalized, brain-extracted T1w image. Usually norm.mgz
flag: %s, position: -2
label: (a unicode string or an integer (int or long), nipype default
value: wm)
label to be picked up, can be a Freesurfer's string like 'wm' or a
label value (e.g. 127 for rh or 255 for lh)
flag: %s, position: -3
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
keep: (a boolean)
keep WM edits
flag: -keep
nocorners: (a boolean)
do not remove corner configurations in addition to edge ones.
flag: -nocorners
out_file: (a file name)
the output file after mri_pretess.
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
test: (a boolean)
adds a voxel that should be removed by mri_pretess. The value of the
voxel is set to that of an ON-edited WM, so it should be kept with
-keep. The output will NOT be saved.
flag: -test
Outputs:
out_file: (an existing file name)
output file after mri_pretess
MRITessellate¶
Wraps command mri_tessellate
Uses Freesurfer’s mri_tessellate to create surfaces by tessellating a given input volume
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> tess = fs.MRITessellate()
>>> tess.inputs.in_file = 'aseg.mgz'
>>> tess.inputs.label_value = 17
>>> tess.inputs.out_file = 'lh.hippocampus'
>>> tess.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
Input volume to tesselate voxels from.
flag: %s, position: -3
label_value: (an integer (int or long))
Label value which to tesselate from the input volume. (integer, if
input is "filled.mgz" volume, 127 is rh, 255 is lh)
flag: %d, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
output filename or True to generate one
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
tesselate_all_voxels: (a boolean)
Tessellate the surface of all voxels with different labels
flag: -a
use_real_RAS_coordinates: (a boolean)
Saves surface with real RAS coordinates where c_(r,a,s) != 0
flag: -n
Outputs:
surface: (an existing file name)
binary surface of the tessellation
MRIsCalc¶
Wraps command mris_calc
‘mris_calc’ is a simple calculator that operates on FreeSurfer curvatures and volumes. In most cases, the calculator functions with three arguments: two inputs and an <ACTION> linking them. Some actions, however, operate with only one input <file1>. In all cases, the first input <file1> is the name of a FreeSurfer curvature overlay (e.g. rh.curv) or volume file (e.g. orig.mgz). For two inputs, the calculator first assumes that the second input is a file. If, however, this second input file doesn’t exist, the calculator assumes it refers to a float number, which is then processed according to <ACTION>.Note: <file1> and <file2> should typically be generated on the same subject.
Examples¶
>>> from nipype.interfaces.freesurfer import MRIsCalc
>>> example = MRIsCalc()
>>> example.inputs.in_file1 = 'lh.area'
>>> example.inputs.in_file2 = 'lh.area.pial'
>>> example.inputs.action = 'add'
>>> example.inputs.out_file = 'area.mid'
>>> example.cmdline
'mris_calc -o lh.area.mid lh.area add lh.area.pial'
Inputs:
[Mandatory]
action: (a string)
Action to perform on input file(s)
flag: %s, position: -2
in_file1: (an existing file name)
Input file 1
flag: %s, position: -3
out_file: (a file name)
Output file after calculation
flag: -o %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
in_file2: (an existing file name)
Input file 2
flag: %s, position: -1
mutually_exclusive: in_float, in_int
in_float: (a float)
Input float
flag: %f, position: -1
mutually_exclusive: in_file2, in_int
in_int: (an integer (int or long))
Input integer
flag: %d, position: -1
mutually_exclusive: in_file2, in_float
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file after calculation
MRIsCombine¶
Wraps command mris_convert
Uses Freesurfer’s mris_convert to combine two surface files into one.
For complete details, see the mris_convert Documentation.
If given an out_file that does not begin with 'lh.' or 'rh.',
mris_convert will prepend 'lh.' to the file name.
To avoid this behavior, consider setting out_file = './<filename>', or
leaving out_file blank.
In a Node/Workflow, out_file is interpreted literally.
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> mris = fs.MRIsCombine()
>>> mris.inputs.in_files = ['lh.pial', 'rh.pial']
>>> mris.inputs.out_file = 'bh.pial'
>>> mris.cmdline
'mris_convert --combinesurfs lh.pial rh.pial bh.pial'
>>> mris.run()
Inputs:
[Mandatory]
in_files: (a list of from 2 to 2 items which are a file name)
Two surfaces to be combined.
flag: --combinesurfs %s, position: 1
out_file: (a file name)
Output filename. Combined surfaces from in_files.
flag: %s, position: -1
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (an existing file name)
Output filename. Combined surfaces from in_files.
MRIsConvert¶
Wraps command mris_convert
Uses Freesurfer’s mris_convert to convert surface files to various formats
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> mris = fs.MRIsConvert()
>>> mris.inputs.in_file = 'lh.pial'
>>> mris.inputs.out_datatype = 'gii'
>>> mris.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
File to read/convert
flag: %s, position: -2
out_datatype: ('asc' or 'ico' or 'tri' or 'stl' or 'vtk' or 'gii' or
'mgh' or 'mgz')
These file formats are supported: ASCII: .ascICO: .ico, .tri GEO:
.geo STL: .stl VTK: .vtk GIFTI: .gii MGH surface-encoded 'volume':
.mgh, .mgz
mutually_exclusive: out_file
out_file: (a file name)
output filename or True to generate one
flag: %s, position: -1
mutually_exclusive: out_datatype
[Optional]
annot_file: (an existing file name)
input is annotation or gifti label data
flag: --annot %s
args: (a unicode string)
Additional parameters to the command
flag: %s
dataarray_num: (an integer (int or long))
if input is gifti, 'num' specifies which data array to use
flag: --da_num %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
functional_file: (an existing file name)
input is functional time-series or other multi-frame data (must
specify surface)
flag: -f %s
label_file: (an existing file name)
infile is .label file, label is name of this label
flag: --label %s
labelstats_outfile: (a file name)
outfile is name of gifti file to which label stats will be written
flag: --labelstats %s
normal: (a boolean)
output is an ascii file where vertex data
flag: -n
origname: (a string)
read orig positions
flag: -o %s
parcstats_file: (an existing file name)
infile is name of text file containing label/val pairs
flag: --parcstats %s
patch: (a boolean)
input is a patch, not a full surface
flag: -p
rescale: (a boolean)
rescale vertex xyz so total area is same as group average
flag: -r
scalarcurv_file: (an existing file name)
input is scalar curv overlay file (must still specify surface)
flag: -c %s
scale: (a float)
scale vertex xyz by scale
flag: -s %.3f
subjects_dir: (an existing directory name)
subjects directory
talairachxfm_subjid: (a string)
apply talairach xfm of subject to vertex xyz
flag: -t %s
to_scanner: (a boolean)
convert coordinates from native FS (tkr) coords to scanner coords
flag: --to-scanner
to_tkr: (a boolean)
convert coordinates from scanner coords to native FS (tkr) coords
flag: --to-tkr
vertex: (a boolean)
Writes out neighbors of a vertex in each row
flag: -v
xyz_ascii: (a boolean)
Print only surface xyz to ascii file
flag: -a
Outputs:
converted: (an existing file name)
converted output surface
MRIsExpand¶
Wraps command mris_expand
Expands a surface (typically ?h.white) outwards while maintaining smoothness and self-intersection constraints.
Examples¶
>>> from nipype.interfaces.freesurfer import MRIsExpand
>>> mris_expand = MRIsExpand(thickness=True, distance=0.5)
>>> mris_expand.inputs.in_file = 'lh.white'
>>> mris_expand.cmdline
'mris_expand -thickness lh.white 0.5 expanded'
>>> mris_expand.inputs.out_name = 'graymid'
>>> mris_expand.cmdline
'mris_expand -thickness lh.white 0.5 graymid'
Inputs:
[Mandatory]
distance: (a float)
Distance in mm or fraction of cortical thickness
flag: %g, position: -2
in_file: (an existing file name)
Surface to expand
flag: %s, position: -3
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
dt: (a float)
dt (implicit: 0.25)
flag: -T %g
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
nsurfaces: (an integer (int or long))
Number of surfacces to write during expansion
flag: -N %d
out_name: (a unicode string, nipype default value: expanded)
Output surface file
If no path, uses directory of `in_file`
If no path AND missing "lh." or "rh.", derive from `in_file`
flag: %s, position: -1
pial: (a unicode string)
Name of pial file (implicit: "pial")
If no path, uses directory of `in_file`
If no path AND missing "lh." or "rh.", derive from `in_file`
flag: -pial %s
smooth_averages: (an integer (int or long))
Smooth surface with N iterations after expansion
flag: -A %d
sphere: (a unicode string, nipype default value: sphere)
WARNING: Do not change this trait
spring: (a float)
Spring term (implicit: 0.05)
flag: -S %g
subjects_dir: (an existing directory name)
subjects directory
thickness: (a boolean)
Expand by fraction of cortical thickness, not mm
flag: -thickness
thickness_name: (a unicode string)
Name of thickness file (implicit: "thickness")
If no path, uses directory of `in_file`
If no path AND missing "lh." or "rh.", derive from `in_file`
flag: -thickness_name %s
write_iterations: (an integer (int or long))
Write snapshots of expansion every N iterations
flag: -W %d
Outputs:
out_file: (a file name)
Output surface file
MRIsInflate¶
Wraps command mris_inflate
This program will inflate a cortical surface.
Examples¶
>>> from nipype.interfaces.freesurfer import MRIsInflate
>>> inflate = MRIsInflate()
>>> inflate.inputs.in_file = 'lh.pial'
>>> inflate.inputs.no_save_sulc = True
>>> inflate.cmdline
'mris_inflate -no-save-sulc lh.pial lh.inflated'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for MRIsInflate
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
no_save_sulc: (a boolean)
Do not save sulc file as output
flag: -no-save-sulc
mutually_exclusive: out_sulc
out_file: (a file name)
Output file for MRIsInflate
flag: %s, position: -1
out_sulc: (a file name)
Output sulc file
mutually_exclusive: no_save_sulc
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file for MRIsInflate
out_sulc: (a file name)
Output sulc file
MakeAverageSubject¶
Wraps command make_average_subject
Make an average freesurfer subject
Examples¶
>>> from nipype.interfaces.freesurfer import MakeAverageSubject
>>> avg = MakeAverageSubject(subjects_ids=['s1', 's2'])
>>> avg.cmdline
'make_average_subject --out average --subjects s1 s2'
Inputs:
[Mandatory]
subjects_ids: (a list of items which are a unicode string)
freesurfer subjects ids to average
flag: --subjects %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_name: (a file name, nipype default value: average)
name for the average subject
flag: --out %s
subjects_dir: (an existing directory name)
subjects directory
Outputs:
average_subject_name: (a unicode string)
Output registration file
MakeSurfaces¶
Wraps command mris_make_surfaces
This program positions the tessellation of the cortical surface at the white matter surface, then the gray matter surface and generate surface files for these surfaces as well as a ‘curvature’ file for the cortical thickness, and a surface file which approximates layer IV of the cortical sheet.
Examples¶
>>> from nipype.interfaces.freesurfer import MakeSurfaces
>>> makesurfaces = MakeSurfaces()
>>> makesurfaces.inputs.hemisphere = 'lh'
>>> makesurfaces.inputs.subject_id = '10335'
>>> makesurfaces.inputs.in_orig = 'lh.pial'
>>> makesurfaces.inputs.in_wm = 'wm.mgz'
>>> makesurfaces.inputs.in_filled = 'norm.mgz'
>>> makesurfaces.inputs.in_label = 'aparc+aseg.nii'
>>> makesurfaces.inputs.in_T1 = 'T1.mgz'
>>> makesurfaces.inputs.orig_pial = 'lh.pial'
>>> makesurfaces.cmdline
'mris_make_surfaces -T1 T1.mgz -orig pial -orig_pial pial 10335 lh'
Inputs:
[Mandatory]
hemisphere: ('lh' or 'rh')
Hemisphere being processed
flag: %s, position: -1
in_filled: (an existing file name)
Implicit input file filled.mgz
in_orig: (an existing file name)
Implicit input file <hemisphere>.orig
flag: -orig %s
in_wm: (an existing file name)
Implicit input file wm.mgz
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the input
files to the node directory.
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
fix_mtl: (a boolean)
Undocumented flag
flag: -fix_mtl
in_T1: (an existing file name)
Input brain or T1 file
flag: -T1 %s
in_aseg: (an existing file name)
Input segmentation file
flag: -aseg %s
in_label: (an existing file name)
Implicit input label/<hemisphere>.aparc.annot
mutually_exclusive: noaparc
in_white: (an existing file name)
Implicit input that is sometimes used
longitudinal: (a boolean)
No documentation (used for longitudinal processing)
flag: -long
maximum: (a float)
No documentation (used for longitudinal processing)
flag: -max %.1f
mgz: (a boolean)
No documentation. Direct questions to analysis-
bugs@nmr.mgh.harvard.edu
flag: -mgz
no_white: (a boolean)
Undocumented flag
flag: -nowhite
noaparc: (a boolean)
No documentation. Direct questions to analysis-
bugs@nmr.mgh.harvard.edu
flag: -noaparc
mutually_exclusive: in_label
orig_pial: (an existing file name)
Specify a pial surface to start with
flag: -orig_pial %s
requires: in_label
orig_white: (an existing file name)
Specify a white surface to start with
flag: -orig_white %s
subjects_dir: (an existing directory name)
subjects directory
white: (a string)
White surface name
flag: -white %s
white_only: (a boolean)
Undocumented flage
flag: -whiteonly
Outputs:
out_area: (a file name)
Output area file for MakeSurfaces
out_cortex: (a file name)
Output cortex file for MakeSurfaces
out_curv: (a file name)
Output curv file for MakeSurfaces
out_pial: (a file name)
Output pial surface for MakeSurfaces
out_thickness: (a file name)
Output thickness file for MakeSurfaces
out_white: (a file name)
Output white matter hemisphere surface
ParcellationStats¶
Wraps command mris_anatomical_stats
This program computes a number of anatomical properties.
Examples¶
>>> from nipype.interfaces.freesurfer import ParcellationStats
>>> import os
>>> parcstats = ParcellationStats()
>>> parcstats.inputs.subject_id = '10335'
>>> parcstats.inputs.hemisphere = 'lh'
>>> parcstats.inputs.wm = './../mri/wm.mgz'
>>> parcstats.inputs.transform = './../mri/transforms/talairach.xfm'
>>> parcstats.inputs.brainmask = './../mri/brainmask.mgz'
>>> parcstats.inputs.aseg = './../mri/aseg.presurf.mgz'
>>> parcstats.inputs.ribbon = './../mri/ribbon.mgz'
>>> parcstats.inputs.lh_pial = 'lh.pial'
>>> parcstats.inputs.rh_pial = 'lh.pial'
>>> parcstats.inputs.lh_white = 'lh.white'
>>> parcstats.inputs.rh_white = 'rh.white'
>>> parcstats.inputs.thickness = 'lh.thickness'
>>> parcstats.inputs.surface = 'white'
>>> parcstats.inputs.out_table = 'lh.test.stats'
>>> parcstats.inputs.out_color = 'test.ctab'
>>> parcstats.cmdline
'mris_anatomical_stats -c test.ctab -f lh.test.stats 10335 lh white'
Inputs:
[Mandatory]
aseg: (an existing file name)
Input file must be <subject_id>/mri/aseg.presurf.mgz
brainmask: (an existing file name)
Input file must be <subject_id>/mri/brainmask.mgz
hemisphere: ('lh' or 'rh')
Hemisphere being processed
flag: %s, position: -2
lh_pial: (an existing file name)
Input file must be <subject_id>/surf/lh.pial
lh_white: (an existing file name)
Input file must be <subject_id>/surf/lh.white
rh_pial: (an existing file name)
Input file must be <subject_id>/surf/rh.pial
rh_white: (an existing file name)
Input file must be <subject_id>/surf/rh.white
ribbon: (an existing file name)
Input file must be <subject_id>/mri/ribbon.mgz
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: %s, position: -3
thickness: (an existing file name)
Input file must be <subject_id>/surf/?h.thickness
transform: (an existing file name)
Input file must be <subject_id>/mri/transforms/talairach.xfm
wm: (an existing file name)
Input file must be <subject_id>/mri/wm.mgz
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the input
files to the node directory.
cortex_label: (an existing file name)
implicit input file {hemi}.cortex.label
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
in_annotation: (a file name)
compute properties for each label in the annotation file separately
flag: -a %s
mutually_exclusive: in_label
in_cortex: (a file name)
Input cortex label
flag: -cortex %s
in_label: (a file name)
limit calculations to specified label
flag: -l %s
mutually_exclusive: in_annotatoin, out_color
mgz: (a boolean)
Look for mgz files
flag: -mgz
out_color: (a file name)
Output annotation files's colortable to text file
flag: -c %s
mutually_exclusive: in_label
out_table: (a file name)
Table output to tablefile
flag: -f %s
requires: tabular_output
subjects_dir: (an existing directory name)
subjects directory
surface: (a string)
Input surface (e.g. 'white')
flag: %s, position: -1
tabular_output: (a boolean)
Tabular output
flag: -b
th3: (a boolean)
turns on new vertex-wise volume calc for mris_anat_stats
flag: -th3
requires: cortex_label
Outputs:
out_color: (a file name)
Output annotation files's colortable to text file
out_table: (a file name)
Table output to tablefile
RelabelHypointensities¶
Wraps command mri_relabel_hypointensities
Relabel Hypointensities
Examples¶
>>> from nipype.interfaces.freesurfer import RelabelHypointensities
>>> relabelhypos = RelabelHypointensities()
>>> relabelhypos.inputs.lh_white = 'lh.pial'
>>> relabelhypos.inputs.rh_white = 'lh.pial'
>>> relabelhypos.inputs.surf_directory = '.'
>>> relabelhypos.inputs.aseg = 'aseg.mgz'
>>> relabelhypos.cmdline
'mri_relabel_hypointensities aseg.mgz . aseg.hypos.mgz'
Inputs:
[Mandatory]
aseg: (an existing file name)
Input aseg file
flag: %s, position: -3
lh_white: (an existing file name)
Implicit input file must be lh.white
rh_white: (an existing file name)
Implicit input file must be rh.white
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
Output aseg file
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
surf_directory: (a directory name, nipype default value: .)
Directory containing lh.white and rh.white
flag: %s, position: -2
Outputs:
out_file: (a file name)
Output aseg file
flag: %s
RemoveIntersection¶
Wraps command mris_remove_intersection
This program removes the intersection of the given MRI
Examples¶
>>> from nipype.interfaces.freesurfer import RemoveIntersection
>>> ri = RemoveIntersection()
>>> ri.inputs.in_file = 'lh.pial'
>>> ri.cmdline
'mris_remove_intersection lh.pial lh.pial'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for RemoveIntersection
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
Output file for RemoveIntersection
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file for RemoveIntersection
RemoveNeck¶
Wraps command mri_remove_neck
Crops the neck out of the mri image
Examples¶
>>> from nipype.interfaces.freesurfer import TalairachQC
>>> remove_neck = RemoveNeck()
>>> remove_neck.inputs.in_file = 'norm.mgz'
>>> remove_neck.inputs.transform = 'trans.mat'
>>> remove_neck.inputs.template = 'trans.mat'
>>> remove_neck.cmdline
'mri_remove_neck norm.mgz trans.mat trans.mat norm_noneck.mgz'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for RemoveNeck
flag: %s, position: -4
template: (an existing file name)
Input template file for RemoveNeck
flag: %s, position: -2
transform: (an existing file name)
Input transform file for RemoveNeck
flag: %s, position: -3
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
Output file for RemoveNeck
flag: %s, position: -1
radius: (an integer (int or long))
Radius
flag: -radius %d
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file with neck removed
SampleToSurface¶
Wraps command mri_vol2surf
Sample a volume to the cortical surface using Freesurfer’s mri_vol2surf.
You must supply a sampling method, range, and units. You can project either a given distance (in mm) or a given fraction of the cortical thickness at that vertex along the surface normal from the target surface, and then set the value of that vertex to be either the value at that point or the average or maximum value found along the projection vector.
By default, the surface will be saved as a vector with a length equal to the
number of vertices on the target surface. This is not a problem for Freesurfer
programs, but if you intend to use the file with interfaces to another package,
you must set the reshape input to True, which will factor the surface vector
into a matrix with dimensions compatible with proper Nifti files.
Examples¶
>>> import nipype.interfaces.freesurfer as fs
>>> sampler = fs.SampleToSurface(hemi="lh")
>>> sampler.inputs.source_file = "cope1.nii.gz"
>>> sampler.inputs.reg_file = "register.dat"
>>> sampler.inputs.sampling_method = "average"
>>> sampler.inputs.sampling_range = 1
>>> sampler.inputs.sampling_units = "frac"
>>> sampler.cmdline
'mri_vol2surf --hemi lh --o ...lh.cope1.mgz --reg register.dat --projfrac-avg 1.000 --mov cope1.nii.gz'
>>> res = sampler.run()
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
target hemisphere
flag: --hemi %s
mni152reg: (a boolean)
source volume is in MNI152 space
flag: --mni152reg
mutually_exclusive: reg_file, reg_header, mni152reg
projection_stem: (a string)
stem for precomputed linear estimates and volume fractions
mutually_exclusive: sampling_method
reg_file: (an existing file name)
source-to-reference registration file
flag: --reg %s
mutually_exclusive: reg_file, reg_header, mni152reg
reg_header: (a boolean)
register based on header geometry
flag: --regheader %s
mutually_exclusive: reg_file, reg_header, mni152reg
requires: subject_id
sampling_method: ('point' or 'max' or 'average')
how to sample -- at a point or at the max or average over a range
flag: %s
mutually_exclusive: projection_stem
requires: sampling_range, sampling_units
source_file: (an existing file name)
volume to sample values from
flag: --mov %s
[Optional]
apply_rot: (a tuple of the form: (a float, a float, a float))
rotation angles (in degrees) to apply to reg matrix
flag: --rot %.3f %.3f %.3f
apply_trans: (a tuple of the form: (a float, a float, a float))
translation (in mm) to apply to reg matrix
flag: --trans %.3f %.3f %.3f
args: (a unicode string)
Additional parameters to the command
flag: %s
cortex_mask: (a boolean)
mask the target surface with hemi.cortex.label
flag: --cortex
mutually_exclusive: mask_label
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
fix_tk_reg: (a boolean)
make reg matrix round-compatible
flag: --fixtkreg
float2int_method: ('round' or 'tkregister')
method to convert reg matrix values (default is round)
flag: --float2int %s
frame: (an integer (int or long))
save only one frame (0-based)
flag: --frame %d
hits_file: (a boolean or an existing file name)
save image with number of hits at each voxel
flag: --srchit %s
hits_type: ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or
'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or
'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or
'niigz')
hits file type
flag: --srchit_type
ico_order: (an integer (int or long))
icosahedron order when target_subject is 'ico'
flag: --icoorder %d
requires: target_subject
interp_method: ('nearest' or 'trilinear')
interpolation method
flag: --interp %s
mask_label: (an existing file name)
label file to mask output with
flag: --mask %s
mutually_exclusive: cortex_mask
no_reshape: (a boolean)
do not reshape surface vector (default)
flag: --noreshape
mutually_exclusive: reshape
out_file: (a file name)
surface file to write
flag: --o %s
out_type: ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or
'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or
'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or
'niigz' or 'gii')
output file type
flag: --out_type %s
override_reg_subj: (a boolean)
override the subject in the reg file header
flag: --srcsubject %s
requires: subject_id
reference_file: (an existing file name)
reference volume (default is orig.mgz)
flag: --ref %s
reshape: (a boolean)
reshape surface vector to fit in non-mgh format
flag: --reshape
mutually_exclusive: no_reshape
reshape_slices: (an integer (int or long))
number of 'slices' for reshaping
flag: --rf %d
sampling_range: (a float or a tuple of the form: (a float, a float, a
float))
sampling range - a point or a tuple of (min, max, step)
sampling_units: ('mm' or 'frac')
sampling range type -- either 'mm' or 'frac'
scale_input: (a float)
multiple all intensities by scale factor
flag: --scale %.3f
smooth_surf: (a float)
smooth output surface (mm fwhm)
flag: --surf-fwhm %.3f
smooth_vol: (a float)
smooth input volume (mm fwhm)
flag: --fwhm %.3f
subject_id: (a string)
subject id
subjects_dir: (an existing directory name)
subjects directory
surf_reg: (a boolean or a unicode string)
use surface registration to target subject
flag: --surfreg %s
requires: target_subject
surface: (a string)
target surface (default is white)
flag: --surf %s
target_subject: (a string)
sample to surface of different subject than source
flag: --trgsubject %s
vox_file: (a boolean or a file name)
text file with the number of voxels intersecting the surface
flag: --nvox %s
Outputs:
hits_file: (an existing file name)
image with number of hits at each voxel
out_file: (an existing file name)
surface file
vox_file: (an existing file name)
text file with the number of voxels intersecting the surface
SmoothTessellation¶
Wraps command mris_smooth
This program smooths the tessellation of a surface using ‘mris_smooth’
See also
- SurfaceSmooth() Interface
- For smoothing a scalar field along a surface manifold
Example¶
>>> import nipype.interfaces.freesurfer as fs
>>> smooth = fs.SmoothTessellation()
>>> smooth.inputs.in_file = 'lh.hippocampus.stl'
>>> smooth.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
Input volume to tesselate voxels from.
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
curvature_averaging_iterations: (an integer (int or long))
Number of curvature averaging iterations (default=10)
flag: -a %d
disable_estimates: (a boolean)
Disables the writing of curvature and area estimates
flag: -nw
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
gaussian_curvature_norm_steps: (an integer (int or long))
Use Gaussian curvature smoothing
flag: %d
gaussian_curvature_smoothing_steps: (an integer (int or long))
Use Gaussian curvature smoothing
flag: %d
normalize_area: (a boolean)
Normalizes the area after smoothing
flag: -area
out_area_file: (a file name)
Write area to ?h.areaname (default "area")
flag: -b %s
out_curvature_file: (a file name)
Write curvature to ?h.curvname (default "curv")
flag: -c %s
out_file: (a file name)
output filename or True to generate one
flag: %s, position: -1
seed: (an integer (int or long))
Seed for setting random number generator
flag: -seed %d
smoothing_iterations: (an integer (int or long))
Number of smoothing iterations (default=10)
flag: -n %d
snapshot_writing_iterations: (an integer (int or long))
Write snapshot every "n" iterations
flag: -w %d
subjects_dir: (an existing directory name)
subjects directory
use_gaussian_curvature_smoothing: (a boolean)
Use Gaussian curvature smoothing
flag: -g
use_momentum: (a boolean)
Uses momentum
flag: -m
Outputs:
surface: (an existing file name)
Smoothed surface file
Sphere¶
Wraps command mris_sphere
This program will add a template into an average surface
Examples¶
>>> from nipype.interfaces.freesurfer import Sphere
>>> sphere = Sphere()
>>> sphere.inputs.in_file = 'lh.pial'
>>> sphere.cmdline
'mris_sphere lh.pial lh.sphere'
Inputs:
[Mandatory]
in_file: (an existing file name)
Input file for Sphere
flag: %s, position: -2
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
in_smoothwm: (an existing file name)
Input surface required when -q flag is not selected
magic: (a boolean)
No documentation. Direct questions to analysis-
bugs@nmr.mgh.harvard.edu
flag: -q
num_threads: (an integer (int or long))
allows for specifying more threads
out_file: (a file name)
Output file for Sphere
flag: %s, position: -1
seed: (an integer (int or long))
Seed for setting random number generator
flag: -seed %d
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
Output file for Sphere
Surface2VolTransform¶
Wraps command mri_surf2vol
Use FreeSurfer mri_surf2vol to apply a transform.
Examples¶
>>> from nipype.interfaces.freesurfer import Surface2VolTransform
>>> xfm2vol = Surface2VolTransform()
>>> xfm2vol.inputs.source_file = 'lh.cope1.mgz'
>>> xfm2vol.inputs.reg_file = 'register.mat'
>>> xfm2vol.inputs.hemi = 'lh'
>>> xfm2vol.inputs.template_file = 'cope1.nii.gz'
>>> xfm2vol.inputs.subjects_dir = '.'
>>> xfm2vol.cmdline
'mri_surf2vol --hemi lh --volreg register.mat --surfval lh.cope1.mgz --sd . --template cope1.nii.gz --outvol lh.cope1_asVol.nii --vtxvol lh.cope1_asVol_vertex.nii'
>>> res = xfm2vol.run()
Inputs:
[Mandatory]
hemi: (a unicode string)
hemisphere of data
flag: --hemi %s
reg_file: (an existing file name)
tkRAS-to-tkRAS matrix (tkregister2 format)
flag: --volreg %s
mutually_exclusive: subject_id
source_file: (an existing file name)
This is the source of the surface values
flag: --surfval %s
mutually_exclusive: mkmask
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
mkmask: (a boolean)
make a mask instead of loading surface values
flag: --mkmask
mutually_exclusive: source_file
projfrac: (a float)
thickness fraction
flag: --projfrac %s
subject_id: (a unicode string)
subject id
flag: --identity %s
mutually_exclusive: reg_file
subjects_dir: (a unicode string)
freesurfer subjects directory defaults to $SUBJECTS_DIR
flag: --sd %s
surf_name: (a unicode string)
surfname (default is white)
flag: --surf %s
template_file: (an existing file name)
Output template volume
flag: --template %s
transformed_file: (a file name)
Output volume
flag: --outvol %s
vertexvol_file: (a file name)
Path name of the vertex output volume, which is the same as output
volume except that the value of each voxel is the vertex-id that is
mapped to that voxel.
flag: --vtxvol %s
Outputs:
transformed_file: (an existing file name)
Path to output file if used normally
vertexvol_file: (a file name)
vertex map volume path id. Optional
SurfaceSmooth¶
Wraps command mri_surf2surf
Smooth a surface image with mri_surf2surf.
The surface is smoothed by an interative process of averaging the value at each vertex with those of its adjacent neighbors. You may supply either the number of iterations to run or a desired effective FWHM of the smoothing process. If the latter, the underlying program will calculate the correct number of iterations internally.
See also
- SmoothTessellation() Interface
- For smoothing a tessellated surface (e.g. in gifti or .stl)
Examples¶
>>> import nipype.interfaces.freesurfer as fs
>>> smoother = fs.SurfaceSmooth()
>>> smoother.inputs.in_file = "lh.cope1.mgz"
>>> smoother.inputs.subject_id = "subj_1"
>>> smoother.inputs.hemi = "lh"
>>> smoother.inputs.fwhm = 5
>>> smoother.cmdline
'mri_surf2surf --cortex --fwhm 5.0000 --hemi lh --sval lh.cope1.mgz --tval ...lh.cope1_smooth5.mgz --s subj_1'
>>> smoother.run()
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
hemisphere to operate on
flag: --hemi %s
in_file: (a file name)
source surface file
flag: --sval %s
subject_id: (a string)
subject id of surface file
flag: --s %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
cortex: (a boolean, nipype default value: True)
only smooth within $hemi.cortex.label
flag: --cortex
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
fwhm: (a float)
effective FWHM of the smoothing process
flag: --fwhm %.4f
mutually_exclusive: smooth_iters
out_file: (a file name)
surface file to write
flag: --tval %s
reshape: (a boolean)
reshape surface vector to fit in non-mgh format
flag: --reshape
smooth_iters: (an integer (int or long))
iterations of the smoothing process
flag: --smooth %d
mutually_exclusive: fwhm
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (an existing file name)
smoothed surface file
SurfaceSnapshots¶
Wraps command tksurfer
Use Tksurfer to save pictures of the cortical surface.
By default, this takes snapshots of the lateral, medial, ventral,
and dorsal surfaces. See the six_images option to add the
anterior and posterior surfaces.
You may also supply your own tcl script (see the Freesurfer wiki for information on scripting tksurfer). The screenshot stem is set as the environment variable “_SNAPSHOT_STEM”, which you can use in your own scripts.
Node that this interface will not run if you do not have graphics enabled on your system.
Examples¶
>>> import nipype.interfaces.freesurfer as fs
>>> shots = fs.SurfaceSnapshots(subject_id="fsaverage", hemi="lh", surface="pial")
>>> shots.inputs.overlay = "zstat1.nii.gz"
>>> shots.inputs.overlay_range = (2.3, 6)
>>> shots.inputs.overlay_reg = "register.dat"
>>> res = shots.run()
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
hemisphere to visualize
flag: %s, position: 2
subject_id: (a string)
subject to visualize
flag: %s, position: 1
surface: (a string)
surface to visualize
flag: %s, position: 3
[Optional]
annot_file: (an existing file name)
path to annotation file to display
flag: -annotation %s
mutually_exclusive: annot_name
annot_name: (a string)
name of annotation to display (must be in $subject/label directory
flag: -annotation %s
mutually_exclusive: annot_file
args: (a unicode string)
Additional parameters to the command
flag: %s
colortable: (an existing file name)
load colortable file
flag: -colortable %s
demean_overlay: (a boolean)
remove mean from overlay
flag: -zm
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
identity_reg: (a boolean)
use the identity matrix to register the overlay to the surface
flag: -overlay-reg-identity
mutually_exclusive: overlay_reg, identity_reg, mni152_reg
invert_overlay: (a boolean)
invert the overlay display
flag: -invphaseflag 1
label_file: (an existing file name)
path to label file to display
flag: -label %s
mutually_exclusive: label_name
label_name: (a string)
name of label to display (must be in $subject/label directory
flag: -label %s
mutually_exclusive: label_file
label_outline: (a boolean)
draw label/annotation as outline
flag: -label-outline
label_under: (a boolean)
draw label/annotation under overlay
flag: -labels-under
mni152_reg: (a boolean)
use to display a volume in MNI152 space on the average subject
flag: -mni152reg
mutually_exclusive: overlay_reg, identity_reg, mni152_reg
orig_suffix: (a string)
set the orig surface suffix string
flag: -orig %s
overlay: (an existing file name)
load an overlay volume/surface
flag: -overlay %s
requires: overlay_range
overlay_range: (a float or a tuple of the form: (a float, a float) or
a tuple of the form: (a float, a float, a float))
overlay range--either min, (min, max) or (min, mid, max)
flag: %s
overlay_range_offset: (a float)
overlay range will be symettric around offset value
flag: -foffset %.3f
overlay_reg: (a file name)
registration matrix file to register overlay to surface
flag: -overlay-reg %s
mutually_exclusive: overlay_reg, identity_reg, mni152_reg
patch_file: (an existing file name)
load a patch
flag: -patch %s
reverse_overlay: (a boolean)
reverse the overlay display
flag: -revphaseflag 1
screenshot_stem: (a string)
stem to use for screenshot file names
show_color_scale: (a boolean)
display the color scale bar
flag: -colscalebarflag 1
show_color_text: (a boolean)
display text in the color scale bar
flag: -colscaletext 1
show_curv: (a boolean)
show curvature
flag: -curv
mutually_exclusive: show_gray_curv
show_gray_curv: (a boolean)
show curvature in gray
flag: -gray
mutually_exclusive: show_curv
six_images: (a boolean)
also take anterior and posterior snapshots
sphere_suffix: (a string)
set the sphere.reg suffix string
flag: -sphere %s
stem_template_args: (a list of items which are a string)
input names to use as arguments for a string-formated stem template
requires: screenshot_stem
subjects_dir: (an existing directory name)
subjects directory
tcl_script: (an existing file name)
override default screenshot script
flag: %s
truncate_overlay: (a boolean)
truncate the overlay display
flag: -truncphaseflag 1
Outputs:
snapshots: (a list of items which are an existing file name)
tiff images of the surface from different perspectives
SurfaceTransform¶
Wraps command mri_surf2surf
Transform a surface file from one subject to another via a spherical registration.
Both the source and target subject must reside in your Subjects Directory, and they must have been processed with recon-all, unless you are transforming to one of the icosahedron meshes.
Examples¶
>>> from nipype.interfaces.freesurfer import SurfaceTransform
>>> sxfm = SurfaceTransform()
>>> sxfm.inputs.source_file = "lh.cope1.nii.gz"
>>> sxfm.inputs.source_subject = "my_subject"
>>> sxfm.inputs.target_subject = "fsaverage"
>>> sxfm.inputs.hemi = "lh"
>>> sxfm.run()
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
hemisphere to transform
flag: --hemi %s
source_annot_file: (an existing file name)
surface annotation file
flag: --sval-annot %s
mutually_exclusive: source_file
source_file: (an existing file name)
surface file with source values
flag: --sval %s
mutually_exclusive: source_annot_file
source_subject: (a string)
subject id for source surface
flag: --srcsubject %s
target_subject: (a string)
subject id of target surface
flag: --trgsubject %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
out_file: (a file name)
surface file to write
flag: --tval %s
reshape: (a boolean)
reshape output surface to conform with Nifti
flag: --reshape
reshape_factor: (an integer (int or long))
number of slices in reshaped image
flag: --reshape-factor
source_type: ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or
'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or
'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or
'niigz')
source file format
flag: --sfmt %s
requires: source_file
subjects_dir: (an existing directory name)
subjects directory
target_ico_order: (1 or 2 or 3 or 4 or 5 or 6 or 7)
order of the icosahedron if target_subject is 'ico'
flag: --trgicoorder %d
target_type: ('cor' or 'mgh' or 'mgz' or 'minc' or 'analyze' or
'analyze4d' or 'spm' or 'afni' or 'brik' or 'bshort' or 'bfloat' or
'sdt' or 'outline' or 'otl' or 'gdf' or 'nifti1' or 'nii' or
'niigz' or 'gii')
output format
flag: --tfmt %s
Outputs:
out_file: (an existing file name)
transformed surface file
TalairachAVI¶
Wraps command talairach_avi
Front-end for Avi Snyders image registration tool. Computes the talairach transform that maps the input volume to the MNI average_305. This does not add the xfm to the header of the input file. When called by recon-all, the xfm is added to the header after the transform is computed.
Examples¶
>>> from nipype.interfaces.freesurfer import TalairachAVI
>>> example = TalairachAVI()
>>> example.inputs.in_file = 'norm.mgz'
>>> example.inputs.out_file = 'trans.mat'
>>> example.cmdline
'talairach_avi --i norm.mgz --xfm trans.mat'
>>> example.run()
Inputs:
[Mandatory]
in_file: (an existing file name)
input volume
flag: --i %s
out_file: (a file name)
output xfm file
flag: --xfm %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
atlas: (a string)
alternate target atlas (in freesurfer/average dir)
flag: --atlas %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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (a file name)
The output transform for TalairachAVI
out_log: (a file name)
The output log file for TalairachAVI
out_txt: (a file name)
The output text file for TaliarachAVI
TalairachQC¶
Wraps command tal_QC_AZS
Examples¶
>>> from nipype.interfaces.freesurfer import TalairachQC
>>> qc = TalairachQC()
>>> qc.inputs.log_file = 'dirs.txt'
>>> qc.cmdline
'tal_QC_AZS dirs.txt'
Inputs:
[Mandatory]
log_file: (an existing file name)
The log file for TalairachQC
flag: %s, position: 0
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
subjects_dir: (an existing directory name)
subjects directory
Outputs:
log_file: (an existing file name, nipype default value:
output.nipype)
The output log
Tkregister2¶
Wraps command tkregister2
Examples¶
Get transform matrix between orig (tkRAS) and native (scannerRAS) coordinates in Freesurfer. Implements the first step of mapping surfaces to native space in this guide.
>>> from nipype.interfaces.freesurfer import Tkregister2
>>> tk2 = Tkregister2(reg_file='T1_to_native.dat')
>>> tk2.inputs.moving_image = 'T1.mgz'
>>> tk2.inputs.target_image = 'structural.nii'
>>> tk2.inputs.reg_header = True
>>> tk2.cmdline
'tkregister2 --mov T1.mgz --noedit --reg T1_to_native.dat --regheader --targ structural.nii'
>>> tk2.run()
The example below uses tkregister2 without the manual editing stage to convert FSL-style registration matrix (.mat) to FreeSurfer-style registration matrix (.dat)
>>> from nipype.interfaces.freesurfer import Tkregister2
>>> tk2 = Tkregister2()
>>> tk2.inputs.moving_image = 'epi.nii'
>>> tk2.inputs.fsl_in_matrix = 'flirt.mat'
>>> tk2.cmdline
'tkregister2 --fsl flirt.mat --mov epi.nii --noedit --reg register.dat'
>>> tk2.run()
Inputs:
[Mandatory]
moving_image: (an existing file name)
moving volume
flag: --mov %s
reg_file: (a file name, nipype default value: register.dat)
freesurfer-style registration file
flag: --reg %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %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
fsl_in_matrix: (an existing file name)
fsl-style registration input matrix
flag: --fsl %s
fsl_out: (a bool or None or a file name)
compute an FSL-compatible resgitration matrix
flag: --fslregout %s
fstal: (a boolean)
set mov to be tal and reg to be tal xfm
flag: --fstal
mutually_exclusive: target_image, moving_image, reg_file
fstarg: (a boolean)
use subject's T1 as reference
flag: --fstarg
mutually_exclusive: target_image
invert_lta_in: (a boolean)
Invert input LTA before applying
requires: lta_in
invert_lta_out: (a boolean)
Invert input LTA before applying
flag: --ltaout-inv
requires: lta_in
lta_in: (an existing file name)
use a matrix in MNI coordinates as initial registration
flag: --lta %s
lta_out: (a bool or None or a file name)
output registration file (LTA format)
flag: --ltaout %s
movscale: (a float)
adjust registration matrix to scale mov
flag: --movscale %f
noedit: (a boolean, nipype default value: True)
do not open edit window (exit)
flag: --noedit
reg_header: (a boolean)
compute regstration from headers
flag: --regheader
subject_id: (a string)
freesurfer subject ID
flag: --s %s
subjects_dir: (an existing directory name)
subjects directory
target_image: (an existing file name)
target volume
flag: --targ %s
mutually_exclusive: fstarg
xfm: (an existing file name)
use a matrix in MNI coordinates as initial registration
flag: --xfm %s
Outputs:
fsl_file: (a file name)
FSL-style registration file
lta_file: (a file name)
LTA-style registration file
reg_file: (an existing file name)
freesurfer-style registration file
VolumeMask¶
Wraps command mris_volmask
Computes a volume mask, at the same resolution as the <subject>/mri/brain.mgz. The volume mask contains 4 values: LH_WM (default 10), LH_GM (default 100), RH_WM (default 20), RH_GM (default 200). The algorithm uses the 4 surfaces situated in <subject>/surf/ [lh|rh].[white|pial] and labels voxels based on the signed-distance function from the surface.
Examples¶
>>> from nipype.interfaces.freesurfer import VolumeMask
>>> volmask = VolumeMask()
>>> volmask.inputs.left_whitelabel = 2
>>> volmask.inputs.left_ribbonlabel = 3
>>> volmask.inputs.right_whitelabel = 41
>>> volmask.inputs.right_ribbonlabel = 42
>>> volmask.inputs.lh_pial = 'lh.pial'
>>> volmask.inputs.rh_pial = 'lh.pial'
>>> volmask.inputs.lh_white = 'lh.pial'
>>> volmask.inputs.rh_white = 'lh.pial'
>>> volmask.inputs.subject_id = '10335'
>>> volmask.inputs.save_ribbon = True
>>> volmask.cmdline
'mris_volmask --label_left_ribbon 3 --label_left_white 2 --label_right_ribbon 42 --label_right_white 41 --save_ribbon 10335'
Inputs:
[Mandatory]
left_ribbonlabel: (an integer (int or long))
Left cortical ribbon label
flag: --label_left_ribbon %d
left_whitelabel: (an integer (int or long))
Left white matter label
flag: --label_left_white %d
lh_pial: (an existing file name)
Implicit input left pial surface
lh_white: (an existing file name)
Implicit input left white matter surface
rh_pial: (an existing file name)
Implicit input right pial surface
rh_white: (an existing file name)
Implicit input right white matter surface
right_ribbonlabel: (an integer (int or long))
Right cortical ribbon label
flag: --label_right_ribbon %d
right_whitelabel: (an integer (int or long))
Right white matter label
flag: --label_right_white %d
subject_id: (a string, nipype default value: subject_id)
Subject being processed
flag: %s, position: -1
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
aseg: (an existing file name)
Implicit aseg.mgz segmentation. Specify a different aseg by using
the 'in_aseg' input.
mutually_exclusive: in_aseg
copy_inputs: (a boolean)
If running as a node, set this to True.This will copy the implicit
input files to the node directory.
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
in_aseg: (an existing file name)
Input aseg file for VolumeMask
flag: --aseg_name %s
mutually_exclusive: aseg
save_ribbon: (a boolean)
option to save just the ribbon for the hemispheres in the format
?h.ribbon.mgz
flag: --save_ribbon
subjects_dir: (an existing directory name)
subjects directory
Outputs:
lh_ribbon: (a file name)
Output left cortical ribbon mask
out_ribbon: (a file name)
Output cortical ribbon mask
rh_ribbon: (a file name)
Output right cortical ribbon mask
createoutputdirs()¶
create all output directories. If not created, some freesurfer interfaces fail