interfaces.freesurfer.model¶
Binarize¶
Wraps command mri_binarize
Use FreeSurfer mri_binarize to threshold an input volume
Examples¶
>>> binvol = Binarize(in_file='structural.nii', min=10, binary_file='foo_out.nii')
>>> binvol.cmdline
'mri_binarize --o foo_out.nii --i structural.nii --min 10.000000'
Inputs:
[Mandatory]
in_file: (an existing file name)
input volume
flag: --i %s
[Optional]
abs: (a boolean)
take abs of invol first (ie, make unsigned)
flag: --abs
args: (a unicode string)
Additional parameters to the command
flag: %s
bin_col_num: (a boolean)
set binarized voxel value to its column number
flag: --bincol
bin_val: (an integer (int or long))
set vox within thresh to val (default is 1)
flag: --binval %d
bin_val_not: (an integer (int or long))
set vox outside range to val (default is 0)
flag: --binvalnot %d
binary_file: (a file name)
binary output volume
flag: --o %s
count_file: (a boolean or a file name)
save number of hits in ascii file (hits, ntotvox, pct)
flag: --count %s
dilate: (an integer (int or long))
niters: dilate binarization in 3D
flag: --dilate %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
erode: (an integer (int or long))
nerode: erode binarization in 3D (after any dilation)
flag: --erode %d
erode2d: (an integer (int or long))
nerode2d: erode binarization in 2D (after any 3D erosion)
flag: --erode2d %d
frame_no: (an integer (int or long))
use 0-based frame of input (default is 0)
flag: --frame %s
invert: (a boolean)
set binval=0, binvalnot=1
flag: --inv
mask_file: (an existing file name)
must be within mask
flag: --mask maskvol
mask_thresh: (a float)
set thresh for mask
flag: --mask-thresh %f
match: (a list of items which are an integer (int or long))
match instead of threshold
flag: --match %d...
max: (a float)
max thresh
flag: --max %f
mutually_exclusive: wm_ven_csf
merge_file: (an existing file name)
merge with mergevol
flag: --merge %s
min: (a float)
min thresh
flag: --min %f
mutually_exclusive: wm_ven_csf
out_type: ('nii' or 'nii.gz' or 'mgz')
output file type
rmax: (a float)
compute max based on rmax*globalmean
flag: --rmax %f
rmin: (a float)
compute min based on rmin*globalmean
flag: --rmin %f
subjects_dir: (an existing directory name)
subjects directory
ventricles: (a boolean)
set match vals those for aseg ventricles+choroid (not 4th)
flag: --ventricles
wm: (a boolean)
set match vals to 2 and 41 (aseg for cerebral WM)
flag: --wm
wm_ven_csf: (a boolean)
WM and ventricular CSF, including choroid (not 4th)
flag: --wm+vcsf
mutually_exclusive: min, max
zero_edges: (a boolean)
zero the edge voxels
flag: --zero-edges
zero_slice_edge: (a boolean)
zero the edge slice voxels
flag: --zero-slice-edges
Outputs:
binary_file: (an existing file name)
binarized output volume
count_file: (a file name)
ascii file containing number of hits
Concatenate¶
Wraps command mri_concat
Use Freesurfer mri_concat to combine several input volumes into one output volume. Can concatenate by frames, or compute a variety of statistics on the input volumes.
Examples¶
Combine two input volumes into one volume with two frames
>>> concat = Concatenate()
>>> concat.inputs.in_files = ['cont1.nii', 'cont2.nii']
>>> concat.inputs.concatenated_file = 'bar.nii'
>>> concat.cmdline
'mri_concat --o bar.nii --i cont1.nii --i cont2.nii'
Inputs:
[Mandatory]
in_files: (a list of items which are an existing file name)
Individual volumes to be concatenated
flag: --i %s...
[Optional]
add_val: (a float)
Add some amount to the input volume
flag: --add %f
args: (a unicode string)
Additional parameters to the command
flag: %s
combine: (a boolean)
Combine non-zero values into single frame volume
flag: --combine
concatenated_file: (a file name)
Output volume
flag: --o %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
gmean: (an integer (int or long))
create matrix to average Ng groups, Nper=Ntot/Ng
flag: --gmean %d
keep_dtype: (a boolean)
Keep voxelwise precision type (default is float
flag: --keep-datatype
mask_file: (an existing file name)
Mask input with a volume
flag: --mask %s
max_bonfcor: (a boolean)
Compute max and bonferroni correct (assumes -log10(ps))
flag: --max-bonfcor
max_index: (a boolean)
Compute the index of max voxel in concatenated volumes
flag: --max-index
mean_div_n: (a boolean)
compute mean/nframes (good for var)
flag: --mean-div-n
multiply_by: (a float)
Multiply input volume by some amount
flag: --mul %f
multiply_matrix_file: (an existing file name)
Multiply input by an ascii matrix in file
flag: --mtx %s
paired_stats: ('sum' or 'avg' or 'diff' or 'diff-norm' or 'diff-
norm1' or 'diff-norm2')
Compute paired sum, avg, or diff
flag: --paired-%s
sign: ('abs' or 'pos' or 'neg')
Take only pos or neg voxles from input, or take abs
flag: --%s
sort: (a boolean)
Sort each voxel by ascending frame value
flag: --sort
stats: ('sum' or 'var' or 'std' or 'max' or 'min' or 'mean')
Compute the sum, var, std, max, min or mean of the input volumes
flag: --%s
subjects_dir: (an existing directory name)
subjects directory
vote: (a boolean)
Most frequent value at each voxel and fraction of occurances
flag: --vote
Outputs:
concatenated_file: (an existing file name)
Path/name of the output volume
GLMFit¶
Wraps command mri_glmfit
Use FreeSurfer’s mri_glmfit to specify and estimate a general linear model.
Examples¶
>>> glmfit = GLMFit()
>>> glmfit.inputs.in_file = 'functional.nii'
>>> glmfit.inputs.one_sample = True
>>> glmfit.cmdline == 'mri_glmfit --glmdir %s --y functional.nii --osgm'%os.getcwd()
True
Inputs:
[Mandatory]
in_file: (a file name)
input 4D file
flag: --y %s
[Optional]
allow_ill_cond: (a boolean)
allow ill-conditioned design matrices
flag: --illcond
allow_repeated_subjects: (a boolean)
allow subject names to repeat in the fsgd file (must appear before
--fsgd
flag: --allowsubjrep
args: (a unicode string)
Additional parameters to the command
flag: %s
calc_AR1: (a boolean)
compute and save temporal AR1 of residual
flag: --tar1
check_opts: (a boolean)
don't run anything, just check options and exit
flag: --checkopts
compute_log_y: (a boolean)
compute natural log of y prior to analysis
flag: --logy
contrast: (a list of items which are an existing file name)
contrast file
flag: --C %s...
cortex: (a boolean)
use subjects ?h.cortex.label as label
flag: --cortex
mutually_exclusive: label_file
debug: (a boolean)
turn on debugging
flag: --debug
design: (an existing file name)
design matrix file
flag: --X %s
mutually_exclusive: fsgd, design, one_sample
diag: (an integer (int or long))
Gdiag_no : set diagnositc level
flag: --diag %d
diag_cluster: (a boolean)
save sig volume and exit from first sim loop
flag: --diag-cluster
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
fixed_fx_dof: (an integer (int or long))
dof for fixed effects analysis
flag: --ffxdof %d
mutually_exclusive: fixed_fx_dof_file
fixed_fx_dof_file: (a file name)
text file with dof for fixed effects analysis
flag: --ffxdofdat %d
mutually_exclusive: fixed_fx_dof
fixed_fx_var: (an existing file name)
for fixed effects analysis
flag: --yffxvar %s
force_perm: (a boolean)
force perumtation test, even when design matrix is not orthog
flag: --perm-force
fsgd: (a tuple of the form: (an existing file name, 'doss' or
'dods'))
freesurfer descriptor file
flag: --fsgd %s %s
mutually_exclusive: fsgd, design, one_sample
fwhm: (a floating point number >= 0.0)
smooth input by fwhm
flag: --fwhm %f
glm_dir: (a unicode string)
save outputs to dir
flag: --glmdir %s
hemi: ('lh' or 'rh')
surface hemisphere
invert_mask: (a boolean)
invert mask
flag: --mask-inv
label_file: (an existing file name)
use label as mask, surfaces only
flag: --label %s
mutually_exclusive: cortex
mask_file: (an existing file name)
binary mask
flag: --mask %s
no_contrast_ok: (a boolean)
do not fail if no contrasts specified
flag: --no-contrasts-ok
no_est_fwhm: (a boolean)
turn off FWHM output estimation
flag: --no-est-fwhm
no_mask_smooth: (a boolean)
do not mask when smoothing
flag: --no-mask-smooth
no_prune: (a boolean)
do not prune
flag: --no-prune
mutually_exclusive: prunethresh
one_sample: (a boolean)
construct X and C as a one-sample group mean
flag: --osgm
mutually_exclusive: one_sample, fsgd, design, contrast
pca: (a boolean)
perform pca/svd analysis on residual
flag: --pca
per_voxel_reg: (a list of items which are an existing file name)
per-voxel regressors
flag: --pvr %s...
profile: (an integer (int or long))
niters : test speed
flag: --profile %d
prune: (a boolean)
remove voxels that do not have a non-zero value at each frame (def)
flag: --prune
prune_thresh: (a float)
prune threshold. Default is FLT_MIN
flag: --prune_thr %f
mutually_exclusive: noprune
resynth_test: (an integer (int or long))
test GLM by resynthsis
flag: --resynthtest %d
save_cond: (a boolean)
flag to save design matrix condition at each voxel
flag: --save-cond
save_estimate: (a boolean)
save signal estimate (yhat)
flag: --yhat-save
save_res_corr_mtx: (a boolean)
save residual error spatial correlation matrix (eres.scm). Big!
flag: --eres-scm
save_residual: (a boolean)
save residual error (eres)
flag: --eres-save
seed: (an integer (int or long))
used for synthesizing noise
flag: --seed %d
self_reg: (a tuple of the form: (an integer (int or long), an integer
(int or long), an integer (int or long)))
self-regressor from index col row slice
flag: --selfreg %d %d %d
sim_done_file: (a file name)
create file when simulation finished
flag: --sim-done %s
sim_sign: ('abs' or 'pos' or 'neg')
abs, pos, or neg
flag: --sim-sign %s
simulation: (a tuple of the form: ('perm' or 'mc-full' or 'mc-z', an
integer (int or long), a float, a unicode string))
nulltype nsim thresh csdbasename
flag: --sim %s %d %f %s
subject_id: (a unicode string)
subject id for surface geometry
subjects_dir: (an existing directory name)
subjects directory
surf: (a boolean)
analysis is on a surface mesh
flag: --surf %s %s %s
requires: subject_id, hemi
surf_geo: (a unicode string, nipype default value: white)
surface geometry name (e.g. white, pial)
synth: (a boolean)
replace input with gaussian
flag: --synth
uniform: (a tuple of the form: (a float, a float))
use uniform distribution instead of gaussian
flag: --uniform %f %f
var_fwhm: (a floating point number >= 0.0)
smooth variance by fwhm
flag: --var-fwhm %f
vox_dump: (a tuple of the form: (an integer (int or long), an integer
(int or long), an integer (int or long)))
dump voxel GLM and exit
flag: --voxdump %d %d %d
weight_file: (an existing file name)
weight for each input at each voxel
mutually_exclusive: weighted_ls
weight_inv: (a boolean)
invert weights
flag: --w-inv
mutually_exclusive: weighted_ls
weight_sqrt: (a boolean)
sqrt of weights
flag: --w-sqrt
mutually_exclusive: weighted_ls
weighted_ls: (an existing file name)
weighted least squares
flag: --wls %s
mutually_exclusive: weight_file, weight_inv, weight_sqrt
Outputs:
beta_file: (an existing file name)
map of regression coefficients
dof_file: (a file name)
text file with effective degrees-of-freedom for the analysis
error_file: (a file name)
map of residual error
error_stddev_file: (a file name)
map of residual error standard deviation
error_var_file: (a file name)
map of residual error variance
estimate_file: (a file name)
map of the estimated Y values
frame_eigenvectors: (a file name)
matrix of frame eigenvectors from residual PCA
ftest_file: (a list of items which are any value)
map of test statistic values
fwhm_file: (a file name)
text file with estimated smoothness
gamma_file: (a list of items which are any value)
map of contrast of regression coefficients
gamma_var_file: (a list of items which are any value)
map of regression contrast variance
glm_dir: (an existing directory name)
output directory
mask_file: (a file name)
map of the mask used in the analysis
sig_file: (a list of items which are any value)
map of F-test significance (in -log10p)
singular_values: (a file name)
matrix singular values from residual PCA
spatial_eigenvectors: (a file name)
map of spatial eigenvectors from residual PCA
svd_stats_file: (a file name)
text file summarizing the residual PCA
Label2Annot¶
Wraps command mris_label2annot
Converts a set of surface labels to an annotation file
Examples¶
>>> from nipype.interfaces.freesurfer import Label2Annot
>>> l2a = Label2Annot()
>>> l2a.inputs.hemisphere = 'lh'
>>> l2a.inputs.subject_id = '10335'
>>> l2a.inputs.in_labels = ['lh.aparc.label']
>>> l2a.inputs.orig = 'lh.pial'
>>> l2a.inputs.out_annot = 'test'
>>> l2a.cmdline
'mris_label2annot --hemi lh --l lh.aparc.label --a test --s 10335'
Inputs:
[Mandatory]
hemisphere: ('lh' or 'rh')
Input hemisphere
flag: --hemi %s
in_labels: (a list of items which are any value)
List of input label files
flag: --l %s...
orig: (an existing file name)
implicit {hemisphere}.orig
out_annot: (a string)
Name of the annotation to create
flag: --a %s
subject_id: (a string, nipype default value: subject_id)
Subject name/ID
flag: --s %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
color_table: (an existing file name)
File that defines the structure names, their indices, and their
color
flag: --ctab %s
copy_inputs: (a boolean)
copy implicit inputs and create a temp subjects_dir
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_max: (a boolean)
Keep label with highest 'stat' value
flag: --maxstatwinner
subjects_dir: (an existing directory name)
subjects directory
verbose_off: (a boolean)
Turn off overlap and stat override messages
flag: --noverbose
Outputs:
out_file: (an existing file name)
Output annotation file
Label2Label¶
Wraps command mri_label2label
Converts a label in one subject’s space to a label in another subject’s space using either talairach or spherical as an intermediate registration space.
If a source mask is used, then the input label must have been created from a surface (ie, the vertex numbers are valid). The format can be anything supported by mri_convert or curv or paint. Vertices in the source label that do not meet threshold in the mask will be removed from the label.
Examples¶
>>> from nipype.interfaces.freesurfer import Label2Label
>>> l2l = Label2Label()
>>> l2l.inputs.hemisphere = 'lh'
>>> l2l.inputs.subject_id = '10335'
>>> l2l.inputs.sphere_reg = 'lh.pial'
>>> l2l.inputs.white = 'lh.pial'
>>> l2l.inputs.source_subject = 'fsaverage'
>>> l2l.inputs.source_label = 'lh-pial.stl'
>>> l2l.inputs.source_white = 'lh.pial'
>>> l2l.inputs.source_sphere_reg = 'lh.pial'
>>> l2l.cmdline
'mri_label2label --hemi lh --trglabel lh-pial_converted.stl --regmethod surface --srclabel lh-pial.stl --srcsubject fsaverage --trgsubject 10335'
Inputs:
[Mandatory]
hemisphere: ('lh' or 'rh')
Input hemisphere
flag: --hemi %s
source_label: (an existing file name)
Source label
flag: --srclabel %s
source_sphere_reg: (an existing file name)
Implicit input <hemisphere>.sphere.reg
source_subject: (a string)
Source subject name
flag: --srcsubject %s
source_white: (an existing file name)
Implicit input <hemisphere>.white
sphere_reg: (an existing file name)
Implicit input <hemisphere>.sphere.reg
subject_id: (a string, nipype default value: subject_id)
Target subject
flag: --trgsubject %s
white: (an existing file name)
Implicit input <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
out_file: (a file name)
Target label
flag: --trglabel %s
registration_method: ('surface' or 'volume', nipype default value:
surface)
Registration method
flag: --regmethod %s
subjects_dir: (an existing directory name)
subjects directory
Outputs:
out_file: (an existing file name)
Output label
Label2Vol¶
Wraps command mri_label2vol
Make a binary volume from a Freesurfer label
Examples¶
>>> binvol = Label2Vol(label_file='cortex.label', template_file='structural.nii', reg_file='register.dat', fill_thresh=0.5, vol_label_file='foo_out.nii')
>>> binvol.cmdline
'mri_label2vol --fillthresh 0.5 --label cortex.label --reg register.dat --temp structural.nii --o foo_out.nii'
Inputs:
[Mandatory]
annot_file: (an existing file name)
surface annotation file
flag: --annot %s
mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
requires: subject_id, hemi
aparc_aseg: (a boolean)
use aparc+aseg.mgz in subjectdir as seg
flag: --aparc+aseg
mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
label_file: (a list of items which are an existing file name)
list of label files
flag: --label %s...
mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
seg_file: (an existing file name)
segmentation file
flag: --seg %s
mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
template_file: (an existing file name)
output template volume
flag: --temp %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
fill_thresh: (0.0 <= a floating point number <= 1.0)
thresh : between 0 and 1
flag: --fillthresh %g
hemi: ('lh' or 'rh')
hemisphere to use lh or rh
flag: --hemi %s
identity: (a boolean)
set R=I
flag: --identity
mutually_exclusive: reg_file, reg_header, identity
invert_mtx: (a boolean)
Invert the registration matrix
flag: --invertmtx
label_hit_file: (a file name)
file with each frame is nhits for a label
flag: --hits %s
label_voxel_volume: (a float)
volume of each label point (def 1mm3)
flag: --labvoxvol %f
map_label_stat: (a file name)
map the label stats field into the vol
flag: --label-stat %s
native_vox2ras: (a boolean)
use native vox2ras xform instead of tkregister-style
flag: --native-vox2ras
proj: (a tuple of the form: ('abs' or 'frac', a float, a float, a
float))
project along surface normal
flag: --proj %s %f %f %f
requires: subject_id, hemi
reg_file: (an existing file name)
tkregister style matrix VolXYZ = R*LabelXYZ
flag: --reg %s
mutually_exclusive: reg_file, reg_header, identity
reg_header: (an existing file name)
label template volume
flag: --regheader %s
mutually_exclusive: reg_file, reg_header, identity
subject_id: (a unicode string)
subject id
flag: --subject %s
subjects_dir: (an existing directory name)
subjects directory
surface: (a unicode string)
use surface instead of white
flag: --surf %s
vol_label_file: (a file name)
output volume
flag: --o %s
Outputs:
vol_label_file: (an existing file name)
output volume
MRISPreproc¶
Wraps command mris_preproc
Use FreeSurfer mris_preproc to prepare a group of contrasts for a second level analysis
Examples¶
>>> preproc = MRISPreproc()
>>> preproc.inputs.target = 'fsaverage'
>>> preproc.inputs.hemi = 'lh'
>>> preproc.inputs.vol_measure_file = [('cont1.nii', 'register.dat'), ('cont1a.nii', 'register.dat')]
>>> preproc.inputs.out_file = 'concatenated_file.mgz'
>>> preproc.cmdline
'mris_preproc --hemi lh --out concatenated_file.mgz --target fsaverage --iv cont1.nii register.dat --iv cont1a.nii register.dat'
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
hemisphere for source and target
flag: --hemi %s
target: (a unicode string)
target subject name
flag: --target %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
fsgd_file: (an existing file name)
specify subjects using fsgd file
flag: --fsgd %s
mutually_exclusive: subjects, fsgd_file, subject_file
fwhm: (a float)
smooth by fwhm mm on the target surface
flag: --fwhm %f
mutually_exclusive: num_iters
fwhm_source: (a float)
smooth by fwhm mm on the source surface
flag: --fwhm-src %f
mutually_exclusive: num_iters_source
num_iters: (an integer (int or long))
niters : smooth by niters on the target surface
flag: --niters %d
mutually_exclusive: fwhm
num_iters_source: (an integer (int or long))
niters : smooth by niters on the source surface
flag: --niterssrc %d
mutually_exclusive: fwhm_source
out_file: (a file name)
output filename
flag: --out %s
proj_frac: (a float)
projection fraction for vol2surf
flag: --projfrac %s
smooth_cortex_only: (a boolean)
only smooth cortex (ie, exclude medial wall)
flag: --smooth-cortex-only
source_format: (a unicode string)
source format
flag: --srcfmt %s
subject_file: (an existing file name)
file specifying subjects separated by white space
flag: --f %s
mutually_exclusive: subjects, fsgd_file, subject_file
subjects: (a list of items which are any value)
subjects from who measures are calculated
flag: --s %s...
mutually_exclusive: subjects, fsgd_file, subject_file
subjects_dir: (an existing directory name)
subjects directory
surf_area: (a unicode string)
Extract vertex area from subject/surf/hemi.surfname to use as input.
flag: --area %s
mutually_exclusive: surf_measure, surf_measure_file, surf_area
surf_dir: (a unicode string)
alternative directory (instead of surf)
flag: --surfdir %s
surf_measure: (a unicode string)
Use subject/surf/hemi.surf_measure as input
flag: --meas %s
mutually_exclusive: surf_measure, surf_measure_file, surf_area
surf_measure_file: (a list of items which are an existing file name)
file alternative to surfmeas, still requires list of subjects
flag: --is %s...
mutually_exclusive: surf_measure, surf_measure_file, surf_area
vol_measure_file: (a list of items which are a tuple of the form: (an
existing file name, an existing file name))
list of volume measure and reg file tuples
flag: --iv %s %s...
Outputs:
out_file: (a file name)
preprocessed output file
MRISPreprocReconAll¶
Wraps command mris_preproc
Extends MRISPreproc to allow it to be used in a recon-all workflow
Examples¶
>>> preproc = MRISPreprocReconAll()
>>> preproc.inputs.target = 'fsaverage'
>>> preproc.inputs.hemi = 'lh'
>>> preproc.inputs.vol_measure_file = [('cont1.nii', 'register.dat'), ('cont1a.nii', 'register.dat')]
>>> preproc.inputs.out_file = 'concatenated_file.mgz'
>>> preproc.cmdline
'mris_preproc --hemi lh --out concatenated_file.mgz --s subject_id --target fsaverage --iv cont1.nii register.dat --iv cont1a.nii register.dat'
Inputs:
[Mandatory]
hemi: ('lh' or 'rh')
hemisphere for source and target
flag: --hemi %s
target: (a unicode string)
target subject name
flag: --target %s
[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 some implicit
inputs 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
fsgd_file: (an existing file name)
specify subjects using fsgd file
flag: --fsgd %s
mutually_exclusive: subjects, fsgd_file, subject_file
fwhm: (a float)
smooth by fwhm mm on the target surface
flag: --fwhm %f
mutually_exclusive: num_iters
fwhm_source: (a float)
smooth by fwhm mm on the source surface
flag: --fwhm-src %f
mutually_exclusive: num_iters_source
lh_surfreg_target: (a file name)
Implicit target surface registration file
requires: surfreg_files
num_iters: (an integer (int or long))
niters : smooth by niters on the target surface
flag: --niters %d
mutually_exclusive: fwhm
num_iters_source: (an integer (int or long))
niters : smooth by niters on the source surface
flag: --niterssrc %d
mutually_exclusive: fwhm_source
out_file: (a file name)
output filename
flag: --out %s
proj_frac: (a float)
projection fraction for vol2surf
flag: --projfrac %s
rh_surfreg_target: (a file name)
Implicit target surface registration file
requires: surfreg_files
smooth_cortex_only: (a boolean)
only smooth cortex (ie, exclude medial wall)
flag: --smooth-cortex-only
source_format: (a unicode string)
source format
flag: --srcfmt %s
subject_file: (an existing file name)
file specifying subjects separated by white space
flag: --f %s
mutually_exclusive: subjects, fsgd_file, subject_file
subject_id: (a string, nipype default value: subject_id)
subject from whom measures are calculated
flag: --s %s
mutually_exclusive: subjects, fsgd_file, subject_file, subject_id
subjects: (a list of items which are any value)
subjects from who measures are calculated
flag: --s %s...
mutually_exclusive: subjects, fsgd_file, subject_file
subjects_dir: (an existing directory name)
subjects directory
surf_area: (a unicode string)
Extract vertex area from subject/surf/hemi.surfname to use as input.
flag: --area %s
mutually_exclusive: surf_measure, surf_measure_file, surf_area
surf_dir: (a unicode string)
alternative directory (instead of surf)
flag: --surfdir %s
surf_measure: (a unicode string)
Use subject/surf/hemi.surf_measure as input
flag: --meas %s
mutually_exclusive: surf_measure, surf_measure_file, surf_area
surf_measure_file: (an existing file name)
file necessary for surfmeas
flag: --meas %s
mutually_exclusive: surf_measure, surf_measure_file, surf_area
surfreg_files: (a list of items which are an existing file name)
lh and rh input surface registration files
flag: --surfreg %s
requires: lh_surfreg_target, rh_surfreg_target
vol_measure_file: (a list of items which are a tuple of the form: (an
existing file name, an existing file name))
list of volume measure and reg file tuples
flag: --iv %s %s...
Outputs:
out_file: (a file name)
preprocessed output file
MS_LDA¶
Wraps command mri_ms_LDA
Perform LDA reduction on the intensity space of an arbitrary # of FLASH images
Examples¶
>>> grey_label = 2
>>> white_label = 3
>>> zero_value = 1
>>> optimalWeights = MS_LDA(lda_labels=[grey_label, white_label], label_file='label.mgz', weight_file='weights.txt', shift=zero_value, vol_synth_file='synth_out.mgz', conform=True, use_weights=True, images=['FLASH1.mgz', 'FLASH2.mgz', 'FLASH3.mgz'])
>>> optimalWeights.cmdline
'mri_ms_LDA -conform -label label.mgz -lda 2 3 -shift 1 -W -synth synth_out.mgz -weight weights.txt FLASH1.mgz FLASH2.mgz FLASH3.mgz'
Inputs:
[Mandatory]
images: (a list of items which are an existing file name)
list of input FLASH images
flag: %s, position: -1
lda_labels: (a list of from 2 to 2 items which are an integer (int or
long))
pair of class labels to optimize
flag: -lda %s
vol_synth_file: (a file name)
filename for the synthesized output volume
flag: -synth %s
weight_file: (a file name)
filename for the LDA weights (input or output)
flag: -weight %s
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
conform: (a boolean)
Conform the input volumes (brain mask typically already conformed)
flag: -conform
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
label_file: (a file name)
filename of the label volume
flag: -label %s
mask_file: (a file name)
filename of the brain mask volume
flag: -mask %s
shift: (an integer (int or long))
shift all values equal to the given value to zero
flag: -shift %d
subjects_dir: (an existing directory name)
subjects directory
use_weights: (a boolean)
Use the weights from a previously generated weight file
flag: -W
Outputs:
vol_synth_file: (an existing file name)
weight_file: (an existing file name)
OneSampleTTest¶
Wraps command mri_glmfit
Inputs:
[Mandatory]
in_file: (a file name)
input 4D file
flag: --y %s
[Optional]
allow_ill_cond: (a boolean)
allow ill-conditioned design matrices
flag: --illcond
allow_repeated_subjects: (a boolean)
allow subject names to repeat in the fsgd file (must appear before
--fsgd
flag: --allowsubjrep
args: (a unicode string)
Additional parameters to the command
flag: %s
calc_AR1: (a boolean)
compute and save temporal AR1 of residual
flag: --tar1
check_opts: (a boolean)
don't run anything, just check options and exit
flag: --checkopts
compute_log_y: (a boolean)
compute natural log of y prior to analysis
flag: --logy
contrast: (a list of items which are an existing file name)
contrast file
flag: --C %s...
cortex: (a boolean)
use subjects ?h.cortex.label as label
flag: --cortex
mutually_exclusive: label_file
debug: (a boolean)
turn on debugging
flag: --debug
design: (an existing file name)
design matrix file
flag: --X %s
mutually_exclusive: fsgd, design, one_sample
diag: (an integer (int or long))
Gdiag_no : set diagnositc level
flag: --diag %d
diag_cluster: (a boolean)
save sig volume and exit from first sim loop
flag: --diag-cluster
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
fixed_fx_dof: (an integer (int or long))
dof for fixed effects analysis
flag: --ffxdof %d
mutually_exclusive: fixed_fx_dof_file
fixed_fx_dof_file: (a file name)
text file with dof for fixed effects analysis
flag: --ffxdofdat %d
mutually_exclusive: fixed_fx_dof
fixed_fx_var: (an existing file name)
for fixed effects analysis
flag: --yffxvar %s
force_perm: (a boolean)
force perumtation test, even when design matrix is not orthog
flag: --perm-force
fsgd: (a tuple of the form: (an existing file name, 'doss' or
'dods'))
freesurfer descriptor file
flag: --fsgd %s %s
mutually_exclusive: fsgd, design, one_sample
fwhm: (a floating point number >= 0.0)
smooth input by fwhm
flag: --fwhm %f
glm_dir: (a unicode string)
save outputs to dir
flag: --glmdir %s
hemi: ('lh' or 'rh')
surface hemisphere
invert_mask: (a boolean)
invert mask
flag: --mask-inv
label_file: (an existing file name)
use label as mask, surfaces only
flag: --label %s
mutually_exclusive: cortex
mask_file: (an existing file name)
binary mask
flag: --mask %s
no_contrast_ok: (a boolean)
do not fail if no contrasts specified
flag: --no-contrasts-ok
no_est_fwhm: (a boolean)
turn off FWHM output estimation
flag: --no-est-fwhm
no_mask_smooth: (a boolean)
do not mask when smoothing
flag: --no-mask-smooth
no_prune: (a boolean)
do not prune
flag: --no-prune
mutually_exclusive: prunethresh
one_sample: (a boolean)
construct X and C as a one-sample group mean
flag: --osgm
mutually_exclusive: one_sample, fsgd, design, contrast
pca: (a boolean)
perform pca/svd analysis on residual
flag: --pca
per_voxel_reg: (a list of items which are an existing file name)
per-voxel regressors
flag: --pvr %s...
profile: (an integer (int or long))
niters : test speed
flag: --profile %d
prune: (a boolean)
remove voxels that do not have a non-zero value at each frame (def)
flag: --prune
prune_thresh: (a float)
prune threshold. Default is FLT_MIN
flag: --prune_thr %f
mutually_exclusive: noprune
resynth_test: (an integer (int or long))
test GLM by resynthsis
flag: --resynthtest %d
save_cond: (a boolean)
flag to save design matrix condition at each voxel
flag: --save-cond
save_estimate: (a boolean)
save signal estimate (yhat)
flag: --yhat-save
save_res_corr_mtx: (a boolean)
save residual error spatial correlation matrix (eres.scm). Big!
flag: --eres-scm
save_residual: (a boolean)
save residual error (eres)
flag: --eres-save
seed: (an integer (int or long))
used for synthesizing noise
flag: --seed %d
self_reg: (a tuple of the form: (an integer (int or long), an integer
(int or long), an integer (int or long)))
self-regressor from index col row slice
flag: --selfreg %d %d %d
sim_done_file: (a file name)
create file when simulation finished
flag: --sim-done %s
sim_sign: ('abs' or 'pos' or 'neg')
abs, pos, or neg
flag: --sim-sign %s
simulation: (a tuple of the form: ('perm' or 'mc-full' or 'mc-z', an
integer (int or long), a float, a unicode string))
nulltype nsim thresh csdbasename
flag: --sim %s %d %f %s
subject_id: (a unicode string)
subject id for surface geometry
subjects_dir: (an existing directory name)
subjects directory
surf: (a boolean)
analysis is on a surface mesh
flag: --surf %s %s %s
requires: subject_id, hemi
surf_geo: (a unicode string, nipype default value: white)
surface geometry name (e.g. white, pial)
synth: (a boolean)
replace input with gaussian
flag: --synth
uniform: (a tuple of the form: (a float, a float))
use uniform distribution instead of gaussian
flag: --uniform %f %f
var_fwhm: (a floating point number >= 0.0)
smooth variance by fwhm
flag: --var-fwhm %f
vox_dump: (a tuple of the form: (an integer (int or long), an integer
(int or long), an integer (int or long)))
dump voxel GLM and exit
flag: --voxdump %d %d %d
weight_file: (an existing file name)
weight for each input at each voxel
mutually_exclusive: weighted_ls
weight_inv: (a boolean)
invert weights
flag: --w-inv
mutually_exclusive: weighted_ls
weight_sqrt: (a boolean)
sqrt of weights
flag: --w-sqrt
mutually_exclusive: weighted_ls
weighted_ls: (an existing file name)
weighted least squares
flag: --wls %s
mutually_exclusive: weight_file, weight_inv, weight_sqrt
Outputs:
beta_file: (an existing file name)
map of regression coefficients
dof_file: (a file name)
text file with effective degrees-of-freedom for the analysis
error_file: (a file name)
map of residual error
error_stddev_file: (a file name)
map of residual error standard deviation
error_var_file: (a file name)
map of residual error variance
estimate_file: (a file name)
map of the estimated Y values
frame_eigenvectors: (a file name)
matrix of frame eigenvectors from residual PCA
ftest_file: (a list of items which are any value)
map of test statistic values
fwhm_file: (a file name)
text file with estimated smoothness
gamma_file: (a list of items which are any value)
map of contrast of regression coefficients
gamma_var_file: (a list of items which are any value)
map of regression contrast variance
glm_dir: (an existing directory name)
output directory
mask_file: (a file name)
map of the mask used in the analysis
sig_file: (a list of items which are any value)
map of F-test significance (in -log10p)
singular_values: (a file name)
matrix singular values from residual PCA
spatial_eigenvectors: (a file name)
map of spatial eigenvectors from residual PCA
svd_stats_file: (a file name)
text file summarizing the residual PCA
SegStats¶
Wraps command mri_segstats
Use FreeSurfer mri_segstats for ROI analysis
Examples¶
>>> import nipype.interfaces.freesurfer as fs
>>> ss = fs.SegStats()
>>> ss.inputs.annot = ('PWS04', 'lh', 'aparc')
>>> ss.inputs.in_file = 'functional.nii'
>>> ss.inputs.subjects_dir = '.'
>>> ss.inputs.avgwf_txt_file = 'avgwf.txt'
>>> ss.inputs.summary_file = 'summary.stats'
>>> ss.cmdline
'mri_segstats --annot PWS04 lh aparc --avgwf ./avgwf.txt --i functional.nii --sum ./summary.stats'
Inputs:
[Mandatory]
annot: (a tuple of the form: (a unicode string, 'lh' or 'rh', a
unicode string))
subject hemi parc : use surface parcellation
flag: --annot %s %s %s
mutually_exclusive: segmentation_file, annot, surf_label
segmentation_file: (an existing file name)
segmentation volume path
flag: --seg %s
mutually_exclusive: segmentation_file, annot, surf_label
surf_label: (a tuple of the form: (a unicode string, 'lh' or 'rh', a
unicode string))
subject hemi label : use surface label
flag: --slabel %s %s %s
mutually_exclusive: segmentation_file, annot, surf_label
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
avgwf_file: (a boolean or a file name)
Save as binary volume (bool or filename)
flag: --avgwfvol %s
avgwf_txt_file: (a boolean or a file name)
Save average waveform into file (bool or filename)
flag: --avgwf %s
brain_vol: ('brain-vol-from-seg' or 'brainmask')
Compute brain volume either with ``brainmask`` or ``brain-vol-from-
seg``
flag: --%s
brainmask_file: (an existing file name)
Load brain mask and compute the volume of the brain as the non-zero
voxels in this volume
flag: --brainmask %s
calc_power: ('sqr' or 'sqrt')
Compute either the sqr or the sqrt of the input
flag: --%s
calc_snr: (a boolean)
save mean/std as extra column in output table
flag: --snr
color_table_file: (an existing file name)
color table file with seg id names
flag: --ctab %s
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
cortex_vol_from_surf: (a boolean)
Compute cortex volume from surf
flag: --surf-ctx-vol
default_color_table: (a boolean)
use $FREESURFER_HOME/FreeSurferColorLUT.txt
flag: --ctab-default
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
empty: (a boolean)
Report on segmentations listed in the color table
flag: --empty
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
etiv: (a boolean)
Compute ICV from talairach transform
flag: --etiv
etiv_only: ('etiv' or 'old-etiv' or '--%s-only')
Compute etiv and exit. Use ``etiv`` or ``old-etiv``
euler: (a boolean)
Write out number of defect holes in orig.nofix based on the euler
number
flag: --euler
exclude_ctx_gm_wm: (a boolean)
exclude cortical gray and white matter
flag: --excl-ctxgmwm
exclude_id: (an integer (int or long))
Exclude seg id from report
flag: --excludeid %d
frame: (an integer (int or long))
Report stats on nth frame of input volume
flag: --frame %d
gca_color_table: (an existing file name)
get color table from GCA (CMA)
flag: --ctab-gca %s
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
in_file: (an existing file name)
Use the segmentation to report stats on this volume
flag: --i %s
in_intensity: (a file name)
Undocumented input norm.mgz file
flag: --in %s --in-intensity-name %s
intensity_units: ('MR')
Intensity units
flag: --in-intensity-units %s
requires: in_intensity
mask_erode: (an integer (int or long))
Erode mask by some amount
flag: --maskerode %d
mask_file: (an existing file name)
Mask volume (same size as seg
flag: --mask %s
mask_frame: (an integer (int or long))
Mask with this (0 based) frame of the mask volume
requires: mask_file
mask_invert: (a boolean)
Invert binarized mask volume
flag: --maskinvert
mask_sign: ('abs' or 'pos' or 'neg' or '--masksign %s')
Sign for mask threshold: pos, neg, or abs
mask_thresh: (a float)
binarize mask with this threshold <0.5>
flag: --maskthresh %f
multiply: (a float)
multiply input by val
flag: --mul %f
non_empty_only: (a boolean)
Only report nonempty segmentations
flag: --nonempty
partial_volume_file: (an existing file name)
Compensate for partial voluming
flag: --pv %s
segment_id: (a list of items which are any value)
Manually specify segmentation ids
flag: --id %s...
sf_avg_file: (a boolean or a file name)
Save mean across space and time
flag: --sfavg %s
subcort_gm: (a boolean)
Compute volume of subcortical gray matter
flag: --subcortgray
subjects_dir: (an existing directory name)
subjects directory
summary_file: (a file name)
Segmentation stats summary table file
flag: --sum %s, position: -1
supratent: (a boolean)
Undocumented input flag
flag: --supratent
total_gray: (a boolean)
Compute volume of total gray matter
flag: --totalgray
vox: (a list of items which are an integer (int or long))
Replace seg with all 0s except at C R S (three int inputs)
flag: --vox %s
wm_vol_from_surf: (a boolean)
Compute wm volume from surf
flag: --surf-wm-vol
Outputs:
avgwf_file: (a file name)
Volume with functional statistics averaged over segs
avgwf_txt_file: (a file name)
Text file with functional statistics averaged over segs
sf_avg_file: (a file name)
Text file with func statistics averaged over segs and framss
summary_file: (an existing file name)
Segmentation summary statistics table
SegStatsReconAll¶
Wraps command mri_segstats
This class inherits SegStats and modifies it for use in a recon-all workflow. This implementation mandates implicit inputs that SegStats. To ensure backwards compatability of SegStats, this class was created.
Examples¶
>>> from nipype.interfaces.freesurfer import SegStatsReconAll
>>> segstatsreconall = SegStatsReconAll()
>>> segstatsreconall.inputs.annot = ('PWS04', 'lh', 'aparc')
>>> segstatsreconall.inputs.avgwf_txt_file = 'avgwf.txt'
>>> segstatsreconall.inputs.summary_file = 'summary.stats'
>>> segstatsreconall.inputs.subject_id = '10335'
>>> segstatsreconall.inputs.ribbon = 'wm.mgz'
>>> segstatsreconall.inputs.transform = 'trans.mat'
>>> segstatsreconall.inputs.presurf_seg = 'wm.mgz'
>>> segstatsreconall.inputs.lh_orig_nofix = 'lh.pial'
>>> segstatsreconall.inputs.rh_orig_nofix = 'lh.pial'
>>> segstatsreconall.inputs.lh_pial = 'lh.pial'
>>> segstatsreconall.inputs.rh_pial = 'lh.pial'
>>> segstatsreconall.inputs.lh_white = 'lh.pial'
>>> segstatsreconall.inputs.rh_white = 'lh.pial'
>>> segstatsreconall.inputs.empty = True
>>> segstatsreconall.inputs.brain_vol = 'brain-vol-from-seg'
>>> segstatsreconall.inputs.exclude_ctx_gm_wm = True
>>> segstatsreconall.inputs.supratent = True
>>> segstatsreconall.inputs.subcort_gm = True
>>> segstatsreconall.inputs.etiv = True
>>> segstatsreconall.inputs.wm_vol_from_surf = True
>>> segstatsreconall.inputs.cortex_vol_from_surf = True
>>> segstatsreconall.inputs.total_gray = True
>>> segstatsreconall.inputs.euler = True
>>> segstatsreconall.inputs.exclude_id = 0
>>> segstatsreconall.cmdline
'mri_segstats --annot PWS04 lh aparc --avgwf ./avgwf.txt --brain-vol-from-seg --surf-ctx-vol --empty --etiv --euler --excl-ctxgmwm --excludeid 0 --subcortgray --subject 10335 --supratent --totalgray --surf-wm-vol --sum ./summary.stats'
Inputs:
[Mandatory]
annot: (a tuple of the form: (a unicode string, 'lh' or 'rh', a
unicode string))
subject hemi parc : use surface parcellation
flag: --annot %s %s %s
mutually_exclusive: segmentation_file, annot, surf_label
lh_orig_nofix: (an existing file name)
Input lh.orig.nofix
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_orig_nofix: (an existing file name)
Input rh.orig.nofix
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: (a file name)
Input file mri/ribbon.mgz
segmentation_file: (an existing file name)
segmentation volume path
flag: --seg %s
mutually_exclusive: segmentation_file, annot, surf_label
subject_id: (a string, nipype default value: subject_id)
Subject id being processed
flag: --subject %s
surf_label: (a tuple of the form: (a unicode string, 'lh' or 'rh', a
unicode string))
subject hemi label : use surface label
flag: --slabel %s %s %s
mutually_exclusive: segmentation_file, annot, surf_label
transform: (an existing file name)
Input transform file
[Optional]
args: (a unicode string)
Additional parameters to the command
flag: %s
aseg: (an existing file name)
Mandatory implicit input in 5.3
avgwf_file: (a boolean or a file name)
Save as binary volume (bool or filename)
flag: --avgwfvol %s
avgwf_txt_file: (a boolean or a file name)
Save average waveform into file (bool or filename)
flag: --avgwf %s
brain_vol: ('brain-vol-from-seg' or 'brainmask')
Compute brain volume either with ``brainmask`` or ``brain-vol-from-
seg``
flag: --%s
brainmask_file: (an existing file name)
Load brain mask and compute the volume of the brain as the non-zero
voxels in this volume
flag: --brainmask %s
calc_power: ('sqr' or 'sqrt')
Compute either the sqr or the sqrt of the input
flag: --%s
calc_snr: (a boolean)
save mean/std as extra column in output table
flag: --snr
color_table_file: (an existing file name)
color table file with seg id names
flag: --ctab %s
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
copy_inputs: (a boolean)
If running as a node, set this to True otherwise, this will copy the
implicit inputs to the node directory.
cortex_vol_from_surf: (a boolean)
Compute cortex volume from surf
flag: --surf-ctx-vol
default_color_table: (a boolean)
use $FREESURFER_HOME/FreeSurferColorLUT.txt
flag: --ctab-default
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
empty: (a boolean)
Report on segmentations listed in the color table
flag: --empty
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
etiv: (a boolean)
Compute ICV from talairach transform
flag: --etiv
etiv_only: ('etiv' or 'old-etiv' or '--%s-only')
Compute etiv and exit. Use ``etiv`` or ``old-etiv``
euler: (a boolean)
Write out number of defect holes in orig.nofix based on the euler
number
flag: --euler
exclude_ctx_gm_wm: (a boolean)
exclude cortical gray and white matter
flag: --excl-ctxgmwm
exclude_id: (an integer (int or long))
Exclude seg id from report
flag: --excludeid %d
frame: (an integer (int or long))
Report stats on nth frame of input volume
flag: --frame %d
gca_color_table: (an existing file name)
get color table from GCA (CMA)
flag: --ctab-gca %s
mutually_exclusive: color_table_file, default_color_table,
gca_color_table
in_file: (an existing file name)
Use the segmentation to report stats on this volume
flag: --i %s
in_intensity: (a file name)
Undocumented input norm.mgz file
flag: --in %s --in-intensity-name %s
intensity_units: ('MR')
Intensity units
flag: --in-intensity-units %s
requires: in_intensity
mask_erode: (an integer (int or long))
Erode mask by some amount
flag: --maskerode %d
mask_file: (an existing file name)
Mask volume (same size as seg
flag: --mask %s
mask_frame: (an integer (int or long))
Mask with this (0 based) frame of the mask volume
requires: mask_file
mask_invert: (a boolean)
Invert binarized mask volume
flag: --maskinvert
mask_sign: ('abs' or 'pos' or 'neg' or '--masksign %s')
Sign for mask threshold: pos, neg, or abs
mask_thresh: (a float)
binarize mask with this threshold <0.5>
flag: --maskthresh %f
multiply: (a float)
multiply input by val
flag: --mul %f
non_empty_only: (a boolean)
Only report nonempty segmentations
flag: --nonempty
partial_volume_file: (an existing file name)
Compensate for partial voluming
flag: --pv %s
presurf_seg: (an existing file name)
Input segmentation volume
segment_id: (a list of items which are any value)
Manually specify segmentation ids
flag: --id %s...
sf_avg_file: (a boolean or a file name)
Save mean across space and time
flag: --sfavg %s
subcort_gm: (a boolean)
Compute volume of subcortical gray matter
flag: --subcortgray
subjects_dir: (an existing directory name)
subjects directory
summary_file: (a file name)
Segmentation stats summary table file
flag: --sum %s, position: -1
supratent: (a boolean)
Undocumented input flag
flag: --supratent
total_gray: (a boolean)
Compute volume of total gray matter
flag: --totalgray
vox: (a list of items which are an integer (int or long))
Replace seg with all 0s except at C R S (three int inputs)
flag: --vox %s
wm_vol_from_surf: (a boolean)
Compute wm volume from surf
flag: --surf-wm-vol
Outputs:
avgwf_file: (a file name)
Volume with functional statistics averaged over segs
avgwf_txt_file: (a file name)
Text file with functional statistics averaged over segs
sf_avg_file: (a file name)
Text file with func statistics averaged over segs and framss
summary_file: (an existing file name)
Segmentation summary statistics table
SphericalAverage¶
Wraps command mris_spherical_average
This program will add a template into an average surface.
Examples¶
>>> from nipype.interfaces.freesurfer import SphericalAverage
>>> sphericalavg = SphericalAverage()
>>> sphericalavg.inputs.out_file = 'test.out'
>>> sphericalavg.inputs.in_average = '.'
>>> sphericalavg.inputs.in_surf = 'lh.pial'
>>> sphericalavg.inputs.hemisphere = 'lh'
>>> sphericalavg.inputs.fname = 'lh.entorhinal'
>>> sphericalavg.inputs.which = 'label'
>>> sphericalavg.inputs.subject_id = '10335'
>>> sphericalavg.inputs.erode = 2
>>> sphericalavg.inputs.threshold = 5
>>> sphericalavg.cmdline
'mris_spherical_average -erode 2 -o 10335 -t 5.0 label lh.entorhinal lh pial . test.out'
Inputs:
[Mandatory]
fname: (a string)
Filename from the average subject directory.
Example: to use rh.entorhinal.label as the input label
filename, set fname to 'rh.entorhinal' and which to
'label'. The program will then search for
'{in_average}/label/rh.entorhinal.label'
flag: %s, position: -5
hemisphere: ('lh' or 'rh')
Input hemisphere
flag: %s, position: -4
in_surf: (an existing file name)
Input surface file
flag: %s, position: -3
subject_id: (a string)
Output subject id
flag: -o %s
which: ('coords' or 'label' or 'vals' or 'curv' or 'area')
No documentation
flag: %s, position: -6
[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
erode: (an integer (int or long))
Undocumented
flag: -erode %d
in_average: (a directory name)
Average subject
flag: %s, position: -2
in_orig: (an existing file name)
Original surface filename
flag: -orig %s
out_file: (a file name)
Output filename
flag: %s, position: -1
subjects_dir: (an existing directory name)
subjects directory
threshold: (a float)
Undocumented
flag: -t %.1f
Outputs:
out_file: (a file name)
Output label