nipype.interfaces.freesurfer.preprocess module

Provides interfaces to various commands provided by FreeSurfer

ApplyVolTransform

Link to code

Bases: FSCommand

Wrapped executable: mri_vol2vol.

Use FreeSurfer mri_vol2vol to apply a transform.

Examples

>>> from nipype.interfaces.freesurfer import ApplyVolTransform
>>> applyreg = ApplyVolTransform()
>>> applyreg.inputs.source_file = 'structural.nii'
>>> applyreg.inputs.reg_file = 'register.dat'
>>> applyreg.inputs.transformed_file = 'struct_warped.nii'
>>> applyreg.inputs.fs_target = True
>>> applyreg.cmdline
'mri_vol2vol --fstarg --reg register.dat --mov structural.nii --o struct_warped.nii'
fs_targeta boolean

Use orig.mgz from subject in regfile as target. Maps to a command-line argument: --fstarg. Mutually exclusive with inputs: target_file, tal, fs_target. Requires inputs: reg_file.

fsl_reg_filea pathlike object or string representing an existing file

FslRAS-to-fslRAS matrix (FSL format). Maps to a command-line argument: --fsl %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

lta_filea pathlike object or string representing an existing file

Linear Transform Array file. Maps to a command-line argument: --lta %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

lta_inv_filea pathlike object or string representing an existing file

LTA, invert. Maps to a command-line argument: --lta-inv %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

mni_152_rega boolean

Target MNI152 space. Maps to a command-line argument: --regheader. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

reg_filea pathlike object or string representing an existing file

TkRAS-to-tkRAS matrix (tkregister2 format). Maps to a command-line argument: --reg %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

reg_headera boolean

ScannerRAS-to-ScannerRAS matrix = identity. Maps to a command-line argument: --regheader. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

source_filea pathlike object or string representing an existing file

Input volume you wish to transform. Maps to a command-line argument: --mov %s.

subjecta string

Set matrix = identity and use subject for any templates. Maps to a command-line argument: --s %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

tala boolean

Map to a sub FOV of MNI305 (with –reg only). Maps to a command-line argument: --tal. Mutually exclusive with inputs: target_file, tal, fs_target.

target_filea pathlike object or string representing an existing file

Output template volume. Maps to a command-line argument: --targ %s. Mutually exclusive with inputs: target_file, tal, fs_target.

xfm_reg_filea pathlike object or string representing an existing file

ScannerRAS-to-ScannerRAS matrix (MNI format). Maps to a command-line argument: --xfm %s. Mutually exclusive with inputs: reg_file, lta_file, lta_inv_file, fsl_reg_file, xfm_reg_file, reg_header, mni_152_reg, subject.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

interp‘trilin’ or ‘nearest’ or ‘cubic’

Interpolation method (<trilin> or nearest). Maps to a command-line argument: --interp %s.

inversea boolean

Sample from target to source. Maps to a command-line argument: --inv.

invert_morpha boolean

Compute and use the inverse of the non-linear morph to resample the input volume. To be used by –m3z. Maps to a command-line argument: --inv-morph. Requires inputs: m3z_file.

m3z_filea pathlike object or string representing a file

This is the morph to be applied to the volume. Unless the morph is in mri/transforms (eg.: for talairach.m3z computed by reconall), you will need to specify the full path to this morph and use the –noDefM3zPath flag. Maps to a command-line argument: --m3z %s.

no_ded_m3z_patha boolean

To be used with the m3z flag. Instructs the code not to look for them3z morph in the default location (SUBJECTS_DIR/subj/mri/transforms), but instead just use the path indicated in –m3z. Maps to a command-line argument: --noDefM3zPath. Requires inputs: m3z_file.

no_resamplea boolean

Do not resample; just change vox2ras matrix. Maps to a command-line argument: --no-resample.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

tal_resolutiona float

Resolution to sample when using tal. Maps to a command-line argument: --talres %.10f.

transformed_filea pathlike object or string representing a file

Output volume. Maps to a command-line argument: --o %s.

transformed_filea pathlike object or string representing an existing file

Path to output file if used normally.

BBRegister

Link to code

Bases: FSCommand

Wrapped executable: bbregister.

Use FreeSurfer bbregister to register a volume to the Freesurfer anatomical.

This program performs within-subject, cross-modal registration using a boundary-based cost function. It is required that you have an anatomical scan of the subject that has already been recon-all-ed using freesurfer.

Examples

>>> from nipype.interfaces.freesurfer import BBRegister
>>> bbreg = BBRegister(subject_id='me', source_file='structural.nii', init='header', contrast_type='t2')
>>> bbreg.cmdline
'bbregister --t2 --init-header --reg structural_bbreg_me.dat --mov structural.nii --s me'
contrast_type‘t1’ or ‘t2’ or ‘bold’ or ‘dti’

Contrast type of image. Maps to a command-line argument: --%s.

source_filea pathlike object or string representing a file

Source file to be registered. Maps to a command-line argument: --mov %s.

subject_ida string

Freesurfer subject id. Maps to a command-line argument: --s %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

dof6 or 9 or 12

Number of transform degrees of freedom. Maps to a command-line argument: --%d.

environa 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’

Environment variables. (Nipype default value: {})

epi_maska boolean

Mask out B0 regions in stages 1 and 2. Maps to a command-line argument: --epi-mask.

fsldofan integer

Degrees of freedom for initial registration (FSL). Maps to a command-line argument: --fsl-dof %d.

init‘coreg’ or ‘rr’ or ‘spm’ or ‘fsl’ or ‘header’ or ‘best’

Initialize registration with mri_coreg, spm, fsl, or header. Maps to a command-line argument: --init-%s. Mutually exclusive with inputs: init_reg_file.

init_cost_filea boolean or a pathlike object or string representing a file

Output initial registration cost file. Maps to a command-line argument: --initcost %s.

init_reg_filea pathlike object or string representing an existing file

Existing registration file. Maps to a command-line argument: --init-reg %s. Mutually exclusive with inputs: init.

intermediate_filea pathlike object or string representing an existing file

Intermediate image, e.g. in case of partial FOV. Maps to a command-line argument: --int %s.

out_fsl_filea boolean or a pathlike object or string representing a file

Write the transformation matrix in FSL FLIRT format. Maps to a command-line argument: --fslmat %s.

out_lta_filea boolean or a pathlike object or string representing a file

Write the transformation matrix in LTA format. Maps to a command-line argument: --lta %s.

out_reg_filea pathlike object or string representing a file

Output registration file. Maps to a command-line argument: --reg %s.

reg_framean integer

0-based frame index for 4D source file. Maps to a command-line argument: --frame %d. Mutually exclusive with inputs: reg_middle_frame.

reg_middle_framea boolean

Register middle frame of 4D source file. Maps to a command-line argument: --mid-frame. Mutually exclusive with inputs: reg_frame.

registered_filea boolean or a pathlike object or string representing a file

Output warped sourcefile either True or filename. Maps to a command-line argument: --o %s.

spm_niftia boolean

Force use of nifti rather than analyze with SPM. Maps to a command-line argument: --spm-nii.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

init_cost_filea pathlike object or string representing an existing file

Output initial registration cost file.

min_cost_filea pathlike object or string representing an existing file

Output registration minimum cost file.

out_fsl_filea pathlike object or string representing an existing file

Output FLIRT-style registration file.

out_lta_filea pathlike object or string representing an existing file

Output LTA-style registration file.

out_reg_filea pathlike object or string representing an existing file

Output registration file.

registered_filea pathlike object or string representing an existing file

Registered and resampled source file.

CALabel

Link to code

Bases: FSCommandOpenMP

Wrapped executable: mri_ca_label.

Label subcortical structures based in GCA model.

See also

For complete details, see the FS Documentation

Examples

>>> from nipype.interfaces import freesurfer
>>> ca_label = freesurfer.CALabel()
>>> ca_label.inputs.in_file = "norm.mgz"
>>> ca_label.inputs.out_file = "out.mgz"
>>> ca_label.inputs.transform = "trans.mat"
>>> ca_label.inputs.template = "Template_6.nii" # in practice use .gcs extension
>>> ca_label.cmdline
'mri_ca_label norm.mgz trans.mat Template_6.nii out.mgz'
in_filea pathlike object or string representing an existing file

Input volume for CALabel. Maps to a command-line argument: %s (position: -4).

out_filea pathlike object or string representing a file

Output file for CALabel. Maps to a command-line argument: %s (position: -1).

templatea pathlike object or string representing an existing file

Input template for CALabel. Maps to a command-line argument: %s (position: -2).

transforma pathlike object or string representing an existing file

Input transform for CALabel. Maps to a command-line argument: %s (position: -3).

aligna boolean

Align CALabel. Maps to a command-line argument: -align.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

asega pathlike object or string representing an existing file

Undocumented flag. Autorecon3 uses ../mri/aseg.presurf.mgz as input file. Maps to a command-line argument: -aseg %s.

environa 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’

Environment variables. (Nipype default value: {})

in_vola pathlike object or string representing an existing file

Set input volume. Maps to a command-line argument: -r %s.

intensitiesa pathlike object or string representing an existing file

Input label intensities file(used in longitudinal processing). Maps to a command-line argument: -r %s.

labela pathlike object or string representing an existing file

Undocumented flag. Autorecon3 uses ../label/{hemisphere}.cortex.label as input file. Maps to a command-line argument: -l %s.

no_big_ventriclesa boolean

No big ventricles. Maps to a command-line argument: -nobigventricles.

num_threadsan integer

Allows for specifying more threads.

priora float

Prior for CALabel. Maps to a command-line argument: -prior %.1f.

relabel_unlikelya tuple of the form: (an integer, a float)

Reclassify voxels at least some std devs from the mean using some size Gaussian window. Maps to a command-line argument: -relabel_unlikely %d %.1f.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing a file

Output volume from CALabel.

CANormalize

Link to code

Bases: FSCommand

Wrapped executable: mri_ca_normalize.

This program creates a normalized volume using the brain volume and an input gca file.

See also

For complete details, see the FS Documentation.

Examples

>>> from nipype.interfaces import freesurfer
>>> ca_normalize = freesurfer.CANormalize()
>>> ca_normalize.inputs.in_file = "T1.mgz"
>>> ca_normalize.inputs.atlas = "atlas.nii.gz" # in practice use .gca atlases
>>> ca_normalize.inputs.transform = "trans.mat" # in practice use .lta transforms
>>> ca_normalize.cmdline
'mri_ca_normalize T1.mgz atlas.nii.gz trans.mat T1_norm.mgz'
atlasa pathlike object or string representing an existing file

The atlas file in gca format. Maps to a command-line argument: %s (position: -3).

in_filea pathlike object or string representing an existing file

The input file for CANormalize. Maps to a command-line argument: %s (position: -4).

transforma pathlike object or string representing an existing file

The transform file in lta format. Maps to a command-line argument: %s (position: -2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

control_pointsa pathlike object or string representing a file

File name for the output control points. Maps to a command-line argument: -c %s.

environa 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’

Environment variables. (Nipype default value: {})

long_filea pathlike object or string representing a file

Undocumented flag used in longitudinal processing. Maps to a command-line argument: -long %s.

maska pathlike object or string representing an existing file

Specifies volume to use as mask. Maps to a command-line argument: -mask %s.

out_filea pathlike object or string representing a file

The output file for CANormalize. Maps to a command-line argument: %s (position: -1).

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

control_pointsa pathlike object or string representing a file

The output control points for Normalize.

out_filea pathlike object or string representing a file

The output file for Normalize.

CARegister

Link to code

Bases: FSCommandOpenMP

Wrapped executable: mri_ca_register.

Generates a multi-dimensional talairach transform from a gca file and talairach.lta file

See also

For complete details, see the FS Documentation

Examples

>>> from nipype.interfaces import freesurfer
>>> ca_register = freesurfer.CARegister()
>>> ca_register.inputs.in_file = "norm.mgz"
>>> ca_register.inputs.out_file = "talairach.m3z"
>>> ca_register.cmdline
'mri_ca_register norm.mgz talairach.m3z'
in_filea pathlike object or string representing an existing file

The input volume for CARegister. Maps to a command-line argument: %s (position: -3).

Aan integer

Undocumented flag used in longitudinal processing. Maps to a command-line argument: -A %d.

aligna string

Specifies when to perform alignment. Maps to a command-line argument: -align-%s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

invert_and_savea boolean

Invert and save the .m3z multi-dimensional talaraich transform to x, y, and z .mgz files. Maps to a command-line argument: -invert-and-save (position: -4).

l_filesa list of items which are a pathlike object or string representing a file

Undocumented flag used in longitudinal processing. Maps to a command-line argument: -l %s.

levelsan integer

Defines how many surrounding voxels will be used in interpolations, default is 6. Maps to a command-line argument: -levels %d.

maska pathlike object or string representing an existing file

Specifies volume to use as mask. Maps to a command-line argument: -mask %s.

no_big_ventriclesa boolean

No big ventricles. Maps to a command-line argument: -nobigventricles.

num_threadsan integer

Allows for specifying more threads.

out_filea pathlike object or string representing a file

The output volume for CARegister. Maps to a command-line argument: %s (position: -1).

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

templatea pathlike object or string representing an existing file

The template file in gca format. Maps to a command-line argument: %s (position: -2).

transforma pathlike object or string representing an existing file

Specifies transform in lta format. Maps to a command-line argument: -T %s.

out_filea pathlike object or string representing a file

The output file for CARegister.

ConcatenateLTA

Link to code

Bases: FSCommand

Wrapped executable: mri_concatenate_lta.

Concatenates two consecutive LTA transformations into one overall transformation

Out = LTA2*LTA1

Examples

>>> from nipype.interfaces.freesurfer import ConcatenateLTA
>>> conc_lta = ConcatenateLTA()
>>> conc_lta.inputs.in_lta1 = 'lta1.lta'
>>> conc_lta.inputs.in_lta2 = 'lta2.lta'
>>> conc_lta.cmdline
'mri_concatenate_lta lta1.lta lta2.lta lta1_concat.lta'

You can use ‘identity.nofile’ as the filename for in_lta2, e.g.:

>>> conc_lta.inputs.in_lta2 = 'identity.nofile'
>>> conc_lta.inputs.invert_1 = True
>>> conc_lta.inputs.out_file = 'inv1.lta'
>>> conc_lta.cmdline
'mri_concatenate_lta -invert1 lta1.lta identity.nofile inv1.lta'

To create a RAS2RAS transform:

>>> conc_lta.inputs.out_type = 'RAS2RAS'
>>> conc_lta.cmdline
'mri_concatenate_lta -invert1 -out_type 1 lta1.lta identity.nofile inv1.lta'
in_lta1a pathlike object or string representing an existing file

Maps some src1 to dst1. Maps to a command-line argument: %s (position: -3).

in_lta2a pathlike object or string representing an existing file or ‘identity.nofile’

Maps dst1(src2) to dst2. Maps to a command-line argument: %s (position: -2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

invert_1a boolean

Invert in_lta1 before applying it. Maps to a command-line argument: -invert1.

invert_2a boolean

Invert in_lta2 before applying it. Maps to a command-line argument: -invert2.

invert_outa boolean

Invert output LTA. Maps to a command-line argument: -invertout.

out_filea pathlike object or string representing a file

The combined LTA maps: src1 to dst2 = LTA2*LTA1. Maps to a command-line argument: %s (position: -1).

out_type‘VOX2VOX’ or ‘RAS2RAS’

Set final LTA type. Maps to a command-line argument: -out_type %d.

subjecta string

Set subject in output LTA. Maps to a command-line argument: -subject %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

tal_source_filea pathlike object or string representing an existing file

If in_lta2 is talairach.xfm, specify source for talairach. Maps to a command-line argument: -tal %s (position: -5). Requires inputs: tal_template_file.

tal_template_filea pathlike object or string representing an existing file

If in_lta2 is talairach.xfm, specify template for talairach. Maps to a command-line argument: %s (position: -4). Requires inputs: tal_source_file.

out_filea pathlike object or string representing a file

The combined LTA maps: src1 to dst2 = LTA2*LTA1.

DICOMConvert

Link to code

Bases: FSCommand

Wrapped executable: mri_convert.

use fs mri_convert to convert dicom files

Examples

>>> from nipype.interfaces.freesurfer import DICOMConvert
>>> cvt = DICOMConvert()
>>> cvt.inputs.dicom_dir = 'dicomdir'
>>> cvt.inputs.file_mapping = [('nifti', '*.nii'), ('info', 'dicom*.txt'), ('dti', '*dti.bv*')]
base_output_dira pathlike object or string representing a directory

Directory in which subject directories are created.

dicom_dira pathlike object or string representing an existing directory

Dicom directory from which to convert dicom files.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

dicom_infoa pathlike object or string representing an existing file

File containing summary information from mri_parse_sdcmdir.

environa 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’

Environment variables. (Nipype default value: {})

file_mappinga list of items which are a tuple of the form: (a string, a string)

Defines the output fields of interface.

ignore_single_slicea boolean

Ignore volumes containing a single slice. Requires inputs: dicom_info.

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’

Defines the type of output file produced. (Nipype default value: niigz)

seq_lista list of items which are a string

List of pulse sequence names to be converted. Requires inputs: dicom_info.

subject_dir_templatea string

Template for subject directory name. (Nipype default value: S.%04d)

subject_idany value

Subject identifier to insert into template.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

property DICOMConvert.cmdline

command plus any arguments (args) validates arguments and generates command line

EditWMwithAseg

Link to code

Bases: FSCommand

Wrapped executable: mri_edit_wm_with_aseg.

Edits a wm file using a segmentation

Examples

>>> from nipype.interfaces.freesurfer import EditWMwithAseg
>>> editwm = EditWMwithAseg()
>>> editwm.inputs.in_file = "T1.mgz"
>>> editwm.inputs.brain_file = "norm.mgz"
>>> editwm.inputs.seg_file = "aseg.mgz"
>>> editwm.inputs.out_file = "wm.asegedit.mgz"
>>> editwm.inputs.keep_in = True
>>> editwm.cmdline
'mri_edit_wm_with_aseg -keep-in T1.mgz norm.mgz aseg.mgz wm.asegedit.mgz'
brain_filea pathlike object or string representing an existing file

Input brain/T1 file. Maps to a command-line argument: %s (position: -3).

in_filea pathlike object or string representing an existing file

Input white matter segmentation file. Maps to a command-line argument: %s (position: -4).

out_filea pathlike object or string representing a file

File to be written as output. Maps to a command-line argument: %s (position: -1).

seg_filea pathlike object or string representing an existing file

Input presurf segmentation file. Maps to a command-line argument: %s (position: -2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

keep_ina boolean

Keep edits as found in input volume. Maps to a command-line argument: -keep-in.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing a file

Output edited WM file.

FitMSParams

Link to code

Bases: FSCommand

Wrapped executable: mri_ms_fitparms.

Estimate tissue parameters from a set of FLASH images.

Examples

>>> from nipype.interfaces.freesurfer import FitMSParams
>>> msfit = FitMSParams()
>>> msfit.inputs.in_files = ['flash_05.mgz', 'flash_30.mgz']
>>> msfit.inputs.out_dir = 'flash_parameters'
>>> msfit.cmdline
'mri_ms_fitparms  flash_05.mgz flash_30.mgz flash_parameters'
in_filesa list of items which are a pathlike object or string representing an existing file

List of FLASH images (must be in mgh format). Maps to a command-line argument: %s (position: -2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

flip_lista list of items which are an integer

List of flip angles of the input files.

out_dira pathlike object or string representing a directory

Directory to store output in. Maps to a command-line argument: %s (position: -1).

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

te_lista list of items which are a float

List of TEs of the input files (in msec).

tr_lista list of items which are an integer

List of TRs of the input files (in msec).

xfm_lista list of items which are a pathlike object or string representing an existing file

List of transform files to apply to each FLASH image.

pd_imagea pathlike object or string representing an existing file

Image of estimated proton density values.

t1_imagea pathlike object or string representing an existing file

Image of estimated T1 relaxation values.

t2star_imagea pathlike object or string representing an existing file

Image of estimated T2* values.

MNIBiasCorrection

Link to code

Bases: FSCommand

Wrapped executable: mri_nu_correct.mni.

Wrapper for nu_correct, a program from the Montreal Neurological Insitute (MNI) used for correcting intensity non-uniformity (ie, bias fields). You must have the MNI software installed on your system to run this. See [www.bic.mni.mcgill.ca/software/N3] for more info.

mri_nu_correct.mni uses float internally instead of uchar. It also rescales the output so that the global mean is the same as that of the input. These two changes are linked and can be turned off with –no-float

Examples

>>> from nipype.interfaces.freesurfer import MNIBiasCorrection
>>> correct = MNIBiasCorrection()
>>> correct.inputs.in_file = "norm.mgz"
>>> correct.inputs.iterations = 6
>>> correct.inputs.protocol_iterations = 1000
>>> correct.inputs.distance = 50
>>> correct.cmdline
'mri_nu_correct.mni --distance 50 --i norm.mgz --n 6 --o norm_output.mgz --proto-iters 1000'

References

[http://freesurfer.net/fswiki/mri_nu_correct.mni] [http://www.bic.mni.mcgill.ca/software/N3] [https://github.com/BIC-MNI/N3]

in_filea pathlike object or string representing an existing file

Input volume. Input can be any format accepted by mri_convert. Maps to a command-line argument: --i %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

distancean integer

N3 -distance option. Maps to a command-line argument: --distance %d.

environa 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’

Environment variables. (Nipype default value: {})

iterationsan integer

Number of iterations to run nu_correct. Default is 4. This is the number of times that nu_correct is repeated (ie, using the output from the previous run as the input for the next). This is different than the -iterations option to nu_correct. Maps to a command-line argument: --n %d. (Nipype default value: 4)

maska pathlike object or string representing an existing file

Brainmask volume. Input can be any format accepted by mri_convert. Maps to a command-line argument: --mask %s.

no_rescalea boolean

Do not rescale so that global mean of output == input global mean. Maps to a command-line argument: --no-rescale.

out_filea pathlike object or string representing a file

Output volume. Output can be any format accepted by mri_convert. If the output format is COR, then the directory must exist. Maps to a command-line argument: --o %s.

protocol_iterationsan integer

Passes Np as argument of the -iterations flag of nu_correct. This is different than the –n flag above. Default is not to pass nu_correct the -iterations flag. Maps to a command-line argument: --proto-iters %d.

shrinkan integer

Shrink parameter for finer sampling (default is 4). Maps to a command-line argument: --shrink %d.

stopa float

Convergence threshold below which iteration stops (suggest 0.01 to 0.0001). Maps to a command-line argument: --stop %f.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

transforma pathlike object or string representing an existing file

Tal.xfm. Use mri_make_uchar instead of conforming. Maps to a command-line argument: --uchar %s.

out_filea pathlike object or string representing an existing file

Output volume.

MRIConvert

Link to code

Bases: FSCommand

Wrapped executable: mri_convert.

use fs mri_convert to manipulate files

Note

Adds niigz as an output type option

Examples

>>> mc = MRIConvert()
>>> mc.inputs.in_file = 'structural.nii'
>>> mc.inputs.out_file = 'outfile.mgz'
>>> mc.inputs.out_type = 'mgz'
>>> mc.cmdline
'mri_convert --out_type mgz --input_volume structural.nii --output_volume outfile.mgz'
in_filea pathlike object or string representing an existing file

File to read/convert. Maps to a command-line argument: --input_volume %s (position: -2).

apply_inv_transforma pathlike object or string representing an existing file

Apply inverse transformation xfm file. Maps to a command-line argument: --apply_inverse_transform %s.

apply_transforma pathlike object or string representing an existing file

Apply xfm file. Maps to a command-line argument: --apply_transform %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

asciia boolean

Save output as ascii col>row>slice>frame. Maps to a command-line argument: --ascii.

autoalign_matrixa pathlike object or string representing an existing file

Text file with autoalign matrix. Maps to a command-line argument: --autoalign %s.

color_filea pathlike object or string representing an existing file

Color file. Maps to a command-line argument: --color_file %s.

conforma boolean

Conform to 1mm voxel size in coronal slice direction with 256^3 or more. Maps to a command-line argument: --conform.

conform_mina boolean

Conform to smallest size. Maps to a command-line argument: --conform_min.

conform_sizea float

Conform to size_in_mm. Maps to a command-line argument: --conform_size %s.

crop_centera tuple of the form: (an integer, an integer, an integer)

<x> <y> <z> crop to 256 around center (x, y, z). Maps to a command-line argument: --crop %d %d %d.

crop_gdfa boolean

Apply GDF cropping. Maps to a command-line argument: --crop_gdf.

crop_sizea tuple of the form: (an integer, an integer, an integer)

<dx> <dy> <dz> crop to size <dx, dy, dz>. Maps to a command-line argument: --cropsize %d %d %d.

cut_endsan integer

Remove ncut slices from the ends. Maps to a command-line argument: --cutends %d.

cw256a boolean

Confrom to dimensions of 256^3. Maps to a command-line argument: --cw256.

devolve_transforma string

Subject id. Maps to a command-line argument: --devolvexfm %s.

drop_nan integer

Drop the last n frames. Maps to a command-line argument: --ndrop %d.

environa 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’

Environment variables. (Nipype default value: {})

fill_parcellationa boolean

Fill parcellation. Maps to a command-line argument: --fill_parcellation.

force_rasa boolean

Use default when orientation info absent. Maps to a command-line argument: --force_ras_good.

framean integer

Keep only 0-based frame number. Maps to a command-line argument: --frame %d.

frame_subsamplea tuple of the form: (an integer, an integer, an integer)

Start delta end : frame subsampling (end = -1 for end). Maps to a command-line argument: --fsubsample %d %d %d.

fwhma float

Smooth input volume by fwhm mm. Maps to a command-line argument: --fwhm %f.

in_centera list of at most 3 items which are a float

<R coordinate> <A coordinate> <S coordinate>. Maps to a command-line argument: --in_center %s.

in_i_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --in_i_direction %f %f %f.

in_i_sizean integer

Input i size. Maps to a command-line argument: --in_i_size %d.

in_infoa boolean

Display input info. Maps to a command-line argument: --in_info.

in_j_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --in_j_direction %f %f %f.

in_j_sizean integer

Input j size. Maps to a command-line argument: --in_j_size %d.

in_k_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --in_k_direction %f %f %f.

in_k_sizean integer

Input k size. Maps to a command-line argument: --in_k_size %d.

in_likea pathlike object or string representing an existing file

Input looks like. Maps to a command-line argument: --in_like %s.

in_matrixa boolean

Display input matrix. Maps to a command-line argument: --in_matrix.

in_orientation‘LAI’ or ‘LIA’ or ‘ALI’ or ‘AIL’ or ‘ILA’ or ‘IAL’ or ‘LAS’ or ‘LSA’ or ‘ALS’ or ‘ASL’ or ‘SLA’ or ‘SAL’ or ‘LPI’ or ‘LIP’ or ‘PLI’ or ‘PIL’ or ‘ILP’ or ‘IPL’ or ‘LPS’ or ‘LSP’ or ‘PLS’ or ‘PSL’ or ‘SLP’ or ‘SPL’ or ‘RAI’ or ‘RIA’ or ‘ARI’ or ‘AIR’ or ‘IRA’ or ‘IAR’ or ‘RAS’ or ‘RSA’ or ‘ARS’ or ‘ASR’ or ‘SRA’ or ‘SAR’ or ‘RPI’ or ‘RIP’ or ‘PRI’ or ‘PIR’ or ‘IRP’ or ‘IPR’ or ‘RPS’ or ‘RSP’ or ‘PRS’ or ‘PSR’ or ‘SRP’ or ‘SPR’

Specify the input orientation. Maps to a command-line argument: --in_orientation %s.

in_scalea float

Input intensity scale factor. Maps to a command-line argument: --scale %f.

in_statsa boolean

Display input stats. Maps to a command-line argument: --in_stats.

in_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 ‘ge’ or ‘gelx’ or ‘lx’ or ‘ximg’ or ‘siemens’ or ‘dicom’ or ‘siemens_dicom’

Input file type. Maps to a command-line argument: --in_type %s.

invert_contrasta float

Threshold for inversting contrast. Maps to a command-line argument: --invert_contrast %f.

midframea boolean

Keep only the middle frame. Maps to a command-line argument: --mid-frame.

no_changea boolean

Don’t change type of input to that of template. Maps to a command-line argument: --nochange.

no_scalea boolean

Dont rescale values for COR. Maps to a command-line argument: --no_scale 1.

no_translatea boolean

???. Maps to a command-line argument: --no_translate.

no_writea boolean

Do not write output. Maps to a command-line argument: --no_write.

out_centera tuple of the form: (a float, a float, a float)

<R coordinate> <A coordinate> <S coordinate>. Maps to a command-line argument: --out_center %f %f %f.

out_datatype‘uchar’ or ‘short’ or ‘int’ or ‘float’

Output data type <uchar|short|int|float>. Maps to a command-line argument: --out_data_type %s.

out_filea pathlike object or string representing a file

Output filename or True to generate one. Maps to a command-line argument: --output_volume %s (position: -1).

out_i_countan integer

Some count ?? in i direction. Maps to a command-line argument: --out_i_count %d.

out_i_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --out_i_direction %f %f %f.

out_i_sizean integer

Output i size. Maps to a command-line argument: --out_i_size %d.

out_infoa boolean

Display output info. Maps to a command-line argument: --out_info.

out_j_countan integer

Some count ?? in j direction. Maps to a command-line argument: --out_j_count %d.

out_j_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --out_j_direction %f %f %f.

out_j_sizean integer

Output j size. Maps to a command-line argument: --out_j_size %d.

out_k_countan integer

Some count ?? in k direction. Maps to a command-line argument: --out_k_count %d.

out_k_dira tuple of the form: (a float, a float, a float)

<R direction> <A direction> <S direction>. Maps to a command-line argument: --out_k_direction %f %f %f.

out_k_sizean integer

Output k size. Maps to a command-line argument: --out_k_size %d.

out_matrixa boolean

Display output matrix. Maps to a command-line argument: --out_matrix.

out_orientation‘LAI’ or ‘LIA’ or ‘ALI’ or ‘AIL’ or ‘ILA’ or ‘IAL’ or ‘LAS’ or ‘LSA’ or ‘ALS’ or ‘ASL’ or ‘SLA’ or ‘SAL’ or ‘LPI’ or ‘LIP’ or ‘PLI’ or ‘PIL’ or ‘ILP’ or ‘IPL’ or ‘LPS’ or ‘LSP’ or ‘PLS’ or ‘PSL’ or ‘SLP’ or ‘SPL’ or ‘RAI’ or ‘RIA’ or ‘ARI’ or ‘AIR’ or ‘IRA’ or ‘IAR’ or ‘RAS’ or ‘RSA’ or ‘ARS’ or ‘ASR’ or ‘SRA’ or ‘SAR’ or ‘RPI’ or ‘RIP’ or ‘PRI’ or ‘PIR’ or ‘IRP’ or ‘IPR’ or ‘RPS’ or ‘RSP’ or ‘PRS’ or ‘PSR’ or ‘SRP’ or ‘SPR’

Specify the output orientation. Maps to a command-line argument: --out_orientation %s.

out_scalea float

Output intensity scale factor. Maps to a command-line argument: --out-scale %d.

out_statsa boolean

Display output stats. Maps to a command-line argument: --out_stats.

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’

Output file type. Maps to a command-line argument: --out_type %s.

parse_onlya boolean

Parse input only. Maps to a command-line argument: --parse_only.

read_onlya boolean

Read the input volume. Maps to a command-line argument: --read_only.

reordera tuple of the form: (an integer, an integer, an integer)

Olddim1 olddim2 olddim3. Maps to a command-line argument: --reorder %d %d %d.

resample_type‘interpolate’ or ‘weighted’ or ‘nearest’ or ‘sinc’ or ‘cubic’

<interpolate|weighted|nearest|sinc|cubic> (default is interpolate). Maps to a command-line argument: --resample_type %s.

reslice_likea pathlike object or string representing an existing file

Reslice output to match file. Maps to a command-line argument: --reslice_like %s.

sdcm_lista pathlike object or string representing an existing file

List of DICOM files for conversion. Maps to a command-line argument: --sdcmlist %s.

skip_nan integer

Skip the first n frames. Maps to a command-line argument: --nskip %d.

slice_biasa float

Apply half-cosine bias field. Maps to a command-line argument: --slice-bias %f.

slice_cropa tuple of the form: (an integer, an integer)

S_start s_end : keep slices s_start to s_end. Maps to a command-line argument: --slice-crop %d %d.

slice_reversea boolean

Reverse order of slices, update vox2ras. Maps to a command-line argument: --slice-reverse.

smooth_parcellationa boolean

Smooth parcellation. Maps to a command-line argument: --smooth_parcellation.

sphinxa boolean

Change orientation info to sphinx. Maps to a command-line argument: --sphinx.

splita boolean

Split output frames into separate output files. Maps to a command-line argument: --split.

status_filea pathlike object or string representing a file

Status file for DICOM conversion. Maps to a command-line argument: --status %s.

subject_namea string

Subject name ???. Maps to a command-line argument: --subject_name %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

tean integer

TE in msec. Maps to a command-line argument: -te %d.

template_infoa boolean

Dump info about template. Maps to a command-line argument: --template_info.

template_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 ‘ge’ or ‘gelx’ or ‘lx’ or ‘ximg’ or ‘siemens’ or ‘dicom’ or ‘siemens_dicom’

Template file type. Maps to a command-line argument: --template_type %s.

tian integer

TI in msec (note upper case flag). Maps to a command-line argument: -ti %d.

tran integer

TR in msec. Maps to a command-line argument: -tr %d.

unwarp_gradienta boolean

Unwarp gradient nonlinearity. Maps to a command-line argument: --unwarp_gradient_nonlinearity.

vox_sizea tuple of the form: (a float, a float, a float)

<size_x> <size_y> <size_z> specify the size (mm) - useful for upsampling or downsampling. Maps to a command-line argument: -voxsize %f %f %f.

zero_ge_z_offseta boolean

Zero ge z offset ???. Maps to a command-line argument: --zero_ge_z_offset.

zero_outlinesa boolean

Zero outlines. Maps to a command-line argument: --zero_outlines.

out_filea list of items which are a pathlike object or string representing an existing file

Converted output file.

MRIConvert.filemap = {'afni': 'brik', 'analyze': 'img', 'analyze4d': 'img', 'bfloat': 'bfloat', 'brik': 'brik', 'bshort': 'bshort', 'cor': 'cor', 'mgh': 'mgh', 'mgz': 'mgz', 'minc': 'mnc', 'nifti1': 'img', 'nii': 'nii', 'niigz': 'nii.gz', 'spm': 'img'}

MRIsCALabel

Link to code

Bases: FSCommandOpenMP

Wrapped executable: mris_ca_label.

For a single subject, produces an annotation file, in which each cortical surface vertex is assigned a neuroanatomical label.This automatic procedure employs data from a previously-prepared atlas file. An atlas file is created from a training set, capturing region data manually drawn by neuroanatomists combined with statistics on variability correlated to geometric information derived from the cortical model (sulcus and curvature). Besides the atlases provided with FreeSurfer, new ones can be prepared using mris_ca_train).

Examples

>>> from nipype.interfaces import freesurfer
>>> ca_label = freesurfer.MRIsCALabel()
>>> ca_label.inputs.subject_id = "test"
>>> ca_label.inputs.hemisphere = "lh"
>>> ca_label.inputs.canonsurf = "lh.pial"
>>> ca_label.inputs.curv = "lh.pial"
>>> ca_label.inputs.sulc = "lh.pial"
>>> ca_label.inputs.classifier = "im1.nii" # in pracice, use .gcs extension
>>> ca_label.inputs.smoothwm = "lh.pial"
>>> ca_label.cmdline
'mris_ca_label test lh lh.pial im1.nii lh.aparc.annot'
canonsurfa pathlike object or string representing an existing file

Input canonical surface file. Maps to a command-line argument: %s (position: -3).

classifiera pathlike object or string representing an existing file

Classifier array input file. Maps to a command-line argument: %s (position: -2).

curva pathlike object or string representing an existing file

Implicit input {hemisphere}.curv.

hemisphere‘lh’ or ‘rh’

Hemisphere (‘lh’ or ‘rh’). Maps to a command-line argument: %s (position: -4).

smoothwma pathlike object or string representing an existing file

Implicit input {hemisphere}.smoothwm.

subject_ida string

Subject name or ID. Maps to a command-line argument: %s (position: -5). (Nipype default value: subject_id)

sulca pathlike object or string representing an existing file

Implicit input {hemisphere}.sulc.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

asega pathlike object or string representing an existing file

Undocumented flag. Autorecon3 uses ../mri/aseg.presurf.mgz as input file. Maps to a command-line argument: -aseg %s.

copy_inputsa boolean

Copies implicit inputs to node directory and creates a temp subjects_directory. Use this when running as a node.

environa 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’

Environment variables. (Nipype default value: {})

labela pathlike object or string representing an existing file

Undocumented flag. Autorecon3 uses ../label/{hemisphere}.cortex.label as input file. Maps to a command-line argument: -l %s.

num_threadsan integer

Allows for specifying more threads.

out_filea pathlike object or string representing a file

Annotated surface output file. Maps to a command-line argument: %s (position: -1).

seedan integer

Maps to a command-line argument: -seed %d.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing a file

Output volume from MRIsCALabel.

MRIsCALabel.run(**inputs)

Execute this interface.

This interface will not raise an exception if runtime.returncode is non-zero.

Parameters:
  • cwd (specify a folder where the interface should be run) –

  • inputs (allows the interface settings to be updated) –

Returns:

results – A copy of the instance that was executed, provenance information and, if successful, results

Return type:

nipype.interfaces.base.support.InterfaceResult

Normalize

Link to code

Bases: FSCommand

Wrapped executable: mri_normalize.

Normalize the white-matter, optionally based on control points. The input volume is converted into a new volume where white matter image values all range around 110.

Examples

>>> from nipype.interfaces import freesurfer
>>> normalize = freesurfer.Normalize()
>>> normalize.inputs.in_file = "T1.mgz"
>>> normalize.inputs.gradient = 1
>>> normalize.cmdline
'mri_normalize -g 1 T1.mgz T1_norm.mgz'
in_filea pathlike object or string representing an existing file

The input file for Normalize. Maps to a command-line argument: %s (position: -2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

gradientan integer

Use max intensity/mm gradient g (default=1). Maps to a command-line argument: -g %d.

maska pathlike object or string representing an existing file

The input mask file for Normalize. Maps to a command-line argument: -mask %s.

out_filea pathlike object or string representing a file

The output file for Normalize. Maps to a command-line argument: %s (position: -1).

segmentationa pathlike object or string representing an existing file

The input segmentation for Normalize. Maps to a command-line argument: -aseg %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

transforma pathlike object or string representing an existing file

Transform file from the header of the input file.

out_filea pathlike object or string representing a file

The output file for Normalize.

ParseDICOMDir

Link to code

Bases: FSCommand

Wrapped executable: mri_parse_sdcmdir.

Uses mri_parse_sdcmdir to get information from dicom directories

Examples

>>> from nipype.interfaces.freesurfer import ParseDICOMDir
>>> dcminfo = ParseDICOMDir()
>>> dcminfo.inputs.dicom_dir = '.'
>>> dcminfo.inputs.sortbyrun = True
>>> dcminfo.inputs.summarize = True
>>> dcminfo.cmdline
'mri_parse_sdcmdir --d . --o dicominfo.txt --sortbyrun --summarize'
dicom_dira pathlike object or string representing an existing directory

Path to siemens dicom directory. Maps to a command-line argument: --d %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

dicom_info_filea pathlike object or string representing a file

File to which results are written. Maps to a command-line argument: --o %s. (Nipype default value: dicominfo.txt)

environa 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’

Environment variables. (Nipype default value: {})

sortbyruna boolean

Assign run numbers. Maps to a command-line argument: --sortbyrun.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

summarizea boolean

Only print out info for run leaders. Maps to a command-line argument: --summarize.

dicom_info_filea pathlike object or string representing an existing file

Text file containing dicom information.

ReconAll

Link to code

Bases: CommandLine

Wrapped executable: recon-all.

Uses recon-all to generate surfaces and parcellations of structural data from anatomical images of a subject.

Examples

>>> from nipype.interfaces.freesurfer import ReconAll
>>> reconall = ReconAll()
>>> reconall.inputs.subject_id = 'foo'
>>> reconall.inputs.directive = 'all'
>>> reconall.inputs.subjects_dir = '.'
>>> reconall.inputs.T1_files = 'structural.nii'
>>> reconall.cmdline
'recon-all -all -i structural.nii -subjid foo -sd .'
>>> reconall.inputs.flags = "-qcache"
>>> reconall.cmdline
'recon-all -all -i structural.nii -qcache -subjid foo -sd .'
>>> reconall.inputs.flags = ["-cw256", "-qcache"]
>>> reconall.cmdline
'recon-all -all -i structural.nii -cw256 -qcache -subjid foo -sd .'

Hemisphere may be specified regardless of directive:

>>> reconall.inputs.flags = []
>>> reconall.inputs.hemi = 'lh'
>>> reconall.cmdline
'recon-all -all -i structural.nii -hemi lh -subjid foo -sd .'

-autorecon-hemi uses the -hemi input to specify the hemisphere to operate upon:

>>> reconall.inputs.directive = 'autorecon-hemi'
>>> reconall.cmdline
'recon-all -autorecon-hemi lh -i structural.nii -subjid foo -sd .'

Hippocampal subfields can accept T1 and T2 images:

>>> reconall_subfields = ReconAll()
>>> reconall_subfields.inputs.subject_id = 'foo'
>>> reconall_subfields.inputs.directive = 'all'
>>> reconall_subfields.inputs.subjects_dir = '.'
>>> reconall_subfields.inputs.T1_files = 'structural.nii'
>>> reconall_subfields.inputs.hippocampal_subfields_T1 = True
>>> reconall_subfields.cmdline
'recon-all -all -i structural.nii -hippocampal-subfields-T1 -subjid foo -sd .'
>>> reconall_subfields.inputs.hippocampal_subfields_T2 = (
... 'structural.nii', 'test')
>>> reconall_subfields.cmdline
'recon-all -all -i structural.nii -hippocampal-subfields-T1T2 structural.nii test -subjid foo -sd .'
>>> reconall_subfields.inputs.hippocampal_subfields_T1 = False
>>> reconall_subfields.cmdline
'recon-all -all -i structural.nii -hippocampal-subfields-T2 structural.nii test -subjid foo -sd .'
FLAIR_filea pathlike object or string representing an existing file

Convert FLAIR image to orig directory. Maps to a command-line argument: -FLAIR %s.

T1_filesa list of items which are a pathlike object or string representing an existing file

Name of T1 file to process. Maps to a command-line argument: -i %s....

T2_filea pathlike object or string representing an existing file

Convert T2 image to orig directory. Maps to a command-line argument: -T2 %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

big_ventriclesa boolean

For use in subjects with enlarged ventricles. Maps to a command-line argument: -bigventricles.

brainstema boolean

Segment brainstem structures. Maps to a command-line argument: -brainstem-structures.

directive‘all’ or ‘autorecon1’ or ‘autorecon2’ or ‘autorecon2-volonly’ or ‘autorecon2-perhemi’ or ‘autorecon2-inflate1’ or ‘autorecon2-cp’ or ‘autorecon2-wm’ or ‘autorecon3’ or ‘autorecon3-T2pial’ or ‘autorecon-pial’ or ‘autorecon-hemi’ or ‘localGI’ or ‘qcache’

Process directive. Maps to a command-line argument: -%s (position: 0). (Nipype default value: all)

environa 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’

Environment variables. (Nipype default value: {})

experta pathlike object or string representing an existing file

Set parameters using expert file. Maps to a command-line argument: -expert %s.

flagsa list of items which are a string

Additional parameters. Maps to a command-line argument: %s.

hemi‘lh’ or ‘rh’

Hemisphere to process. Maps to a command-line argument: -hemi %s.

hippocampal_subfields_T1a boolean

Segment hippocampal subfields using input T1 scan. Maps to a command-line argument: -hippocampal-subfields-T1.

hippocampal_subfields_T2a tuple of the form: (a pathlike object or string representing an existing file, a string)

Segment hippocampal subfields using T2 scan, identified by ID (may be combined with hippocampal_subfields_T1). Maps to a command-line argument: -hippocampal-subfields-T2 %s %s.

hiresa boolean

Conform to minimum voxel size (for voxels < 1mm). Maps to a command-line argument: -hires.

mpragea boolean

Assume scan parameters are MGH MP-RAGE protocol, which produces darker gray matter. Maps to a command-line argument: -mprage.

mri_aparc2asega string

Flags to pass to mri_aparc2aseg commands. Mutually exclusive with inputs: expert.

mri_ca_labela string

Flags to pass to mri_ca_label commands. Mutually exclusive with inputs: expert.

mri_ca_normalizea string

Flags to pass to mri_ca_normalize commands. Mutually exclusive with inputs: expert.

mri_ca_registera string

Flags to pass to mri_ca_register commands. Mutually exclusive with inputs: expert.

mri_edit_wm_with_asega string

Flags to pass to mri_edit_wm_with_aseg commands. Mutually exclusive with inputs: expert.

mri_em_registera string

Flags to pass to mri_em_register commands. Mutually exclusive with inputs: expert.

mri_filla string

Flags to pass to mri_fill commands. Mutually exclusive with inputs: expert.

mri_maska string

Flags to pass to mri_mask commands. Mutually exclusive with inputs: expert.

mri_normalizea string

Flags to pass to mri_normalize commands. Mutually exclusive with inputs: expert.

mri_pretessa string

Flags to pass to mri_pretess commands. Mutually exclusive with inputs: expert.

mri_remove_necka string

Flags to pass to mri_remove_neck commands. Mutually exclusive with inputs: expert.

mri_segmenta string

Flags to pass to mri_segment commands. Mutually exclusive with inputs: expert.

mri_segstatsa string

Flags to pass to mri_segstats commands. Mutually exclusive with inputs: expert.

mri_tessellatea string

Flags to pass to mri_tessellate commands. Mutually exclusive with inputs: expert.

mri_watersheda string

Flags to pass to mri_watershed commands. Mutually exclusive with inputs: expert.

mris_anatomical_statsa string

Flags to pass to mris_anatomical_stats commands. Mutually exclusive with inputs: expert.

mris_ca_labela string

Flags to pass to mris_ca_label commands. Mutually exclusive with inputs: expert.

mris_fix_topologya string

Flags to pass to mris_fix_topology commands. Mutually exclusive with inputs: expert.

mris_inflatea string

Flags to pass to mri_inflate commands. Mutually exclusive with inputs: expert.

mris_make_surfacesa string

Flags to pass to mris_make_surfaces commands. Mutually exclusive with inputs: expert.

mris_registera string

Flags to pass to mris_register commands. Mutually exclusive with inputs: expert.

mris_smootha string

Flags to pass to mri_smooth commands. Mutually exclusive with inputs: expert.

mris_spherea string

Flags to pass to mris_sphere commands. Mutually exclusive with inputs: expert.

mris_surf2vola string

Flags to pass to mris_surf2vol commands. Mutually exclusive with inputs: expert.

mrisp_painta string

Flags to pass to mrisp_paint commands. Mutually exclusive with inputs: expert.

openmpan integer

Number of processors to use in parallel. Maps to a command-line argument: -openmp %d.

parallela boolean

Enable parallel execution. Maps to a command-line argument: -parallel.

subject_ida string

Subject name. Maps to a command-line argument: -subjid %s. (Nipype default value: recon_all)

subjects_dira pathlike object or string representing an existing directory

Path to subjects directory. Maps to a command-line argument: -sd %s.

talairacha string

Flags to pass to talairach commands. Mutually exclusive with inputs: expert.

use_FLAIRa boolean

Use FLAIR image to refine the pial surface. Maps to a command-line argument: -FLAIRpial. Mutually exclusive with inputs: use_T2.

use_T2a boolean

Use T2 image to refine the pial surface. Maps to a command-line argument: -T2pial. Mutually exclusive with inputs: use_FLAIR.

xopts‘use’ or ‘clean’ or ‘overwrite’

Use, delete or overwrite existing expert options file. Maps to a command-line argument: -xopts-%s.

BA_statsa list of items which are a pathlike object or string representing an existing file

Brodmann Area statistics files.

T1a pathlike object or string representing an existing file

Intensity normalized whole-head volume.

annota list of items which are a pathlike object or string representing an existing file

Surface annotation files.

aparc_a2009s_statsa list of items which are a pathlike object or string representing an existing file

Aparc a2009s parcellation statistics files.

aparc_asega list of items which are a pathlike object or string representing an existing file

Aparc parcellation projected into aseg volume.

aparc_statsa list of items which are a pathlike object or string representing an existing file

Aparc parcellation statistics files.

area_piala list of items which are a pathlike object or string representing an existing file

Mean area of triangles each vertex on the pial surface is associated with.

asega pathlike object or string representing an existing file

Volumetric map of regions from automatic segmentation.

aseg_statsa list of items which are a pathlike object or string representing an existing file

Automated segmentation statistics file.

avg_curva list of items which are a pathlike object or string representing an existing file

Average atlas curvature, sampled to subject.

braina pathlike object or string representing an existing file

Intensity normalized brain-only volume.

brainmaska pathlike object or string representing an existing file

Skull-stripped (brain-only) volume.

curva list of items which are a pathlike object or string representing an existing file

Maps of surface curvature.

curv_piala list of items which are a pathlike object or string representing an existing file

Curvature of pial surface.

curv_statsa list of items which are a pathlike object or string representing an existing file

Curvature statistics files.

entorhinal_exvivo_statsa list of items which are a pathlike object or string representing an existing file

Entorhinal exvivo statistics files.

filleda pathlike object or string representing an existing file

Subcortical mass volume.

graymida list of items which are a pathlike object or string representing an existing file

Graymid/midthickness surface meshes.

inflateda list of items which are a pathlike object or string representing an existing file

Inflated surface meshes.

jacobian_whitea list of items which are a pathlike object or string representing an existing file

Distortion required to register to spherical atlas.

labela list of items which are a pathlike object or string representing an existing file

Volume and surface label files.

norma pathlike object or string representing an existing file

Normalized skull-stripped volume.

nua pathlike object or string representing an existing file

Non-uniformity corrected whole-head volume.

origa pathlike object or string representing an existing file

Base image conformed to Freesurfer space.

piala list of items which are a pathlike object or string representing an existing file

Gray matter/pia mater surface meshes.

rawavga pathlike object or string representing an existing file

Volume formed by averaging input images.

ribbona list of items which are a pathlike object or string representing an existing file

Volumetric maps of cortical ribbons.

smoothwma list of items which are a pathlike object or string representing an existing file

Smoothed original surface meshes.

spherea list of items which are a pathlike object or string representing an existing file

Spherical surface meshes.

sphere_rega list of items which are a pathlike object or string representing an existing file

Spherical registration file.

subject_ida string

Subject name for whom to retrieve data.

subjects_dira pathlike object or string representing an existing directory

Freesurfer subjects directory.

sulca list of items which are a pathlike object or string representing an existing file

Surface maps of sulcal depth.

thicknessa list of items which are a pathlike object or string representing an existing file

Surface maps of cortical thickness.

volumea list of items which are a pathlike object or string representing an existing file

Surface maps of cortical volume.

whitea list of items which are a pathlike object or string representing an existing file

White/gray matter surface meshes.

wma pathlike object or string representing an existing file

Segmented white-matter volume.

wmparca pathlike object or string representing an existing file

Aparc parcellation projected into subcortical white matter.

wmparc_statsa list of items which are a pathlike object or string representing an existing file

White matter parcellation statistics file.

property ReconAll.cmdline

command plus any arguments (args) validates arguments and generates command line

ReconAll.force_run = False
property ReconAll.version

interfaces should implement a version property

Resample

Link to code

Bases: FSCommand

Wrapped executable: mri_convert.

Use FreeSurfer mri_convert to up or down-sample image files

Examples

>>> from nipype.interfaces import freesurfer
>>> resampler = freesurfer.Resample()
>>> resampler.inputs.in_file = 'structural.nii'
>>> resampler.inputs.resampled_file = 'resampled.nii'
>>> resampler.inputs.voxel_size = (2.1, 2.1, 2.1)
>>> resampler.cmdline
'mri_convert -vs 2.10 2.10 2.10 -i structural.nii -o resampled.nii'
in_filea pathlike object or string representing an existing file

File to resample. Maps to a command-line argument: -i %s (position: -2).

voxel_sizea tuple of the form: (a float, a float, a float)

Triplet of output voxel sizes. Maps to a command-line argument: -vs %.2f %.2f %.2f.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

resampled_filea pathlike object or string representing a file

Output filename. Maps to a command-line argument: -o %s (position: -1).

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

resampled_filea pathlike object or string representing an existing file

Output filename.

RobustRegister

Link to code

Bases: FSCommand

Wrapped executable: mri_robust_register.

Perform intramodal linear registration (translation and rotation) using robust statistics.

Examples

>>> from nipype.interfaces.freesurfer import RobustRegister
>>> reg = RobustRegister()
>>> reg.inputs.source_file = 'structural.nii'
>>> reg.inputs.target_file = 'T1.nii'
>>> reg.inputs.auto_sens = True
>>> reg.inputs.init_orient = True
>>> reg.cmdline 
'mri_robust_register --satit --initorient --lta .../structural_robustreg.lta --mov structural.nii --dst T1.nii'

References

Reuter, M, Rosas, HD, and Fischl, B, (2010). Highly Accurate Inverse

Consistent Registration: A Robust Approach. Neuroimage 53(4) 1181-96.

auto_sensa boolean

Auto-detect good sensitivity. Maps to a command-line argument: --satit. Mutually exclusive with inputs: outlier_sens.

outlier_sensa float

Set outlier sensitivity explicitly. Maps to a command-line argument: --sat %.4f. Mutually exclusive with inputs: auto_sens.

source_filea pathlike object or string representing an existing file

Volume to be registered. Maps to a command-line argument: --mov %s.

target_filea pathlike object or string representing an existing file

Target volume for the registration. Maps to a command-line argument: --dst %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

est_int_scalea boolean

Estimate intensity scale (recommended for unnormalized images). Maps to a command-line argument: --iscale.

force_doublea boolean

Use double-precision intensities. Maps to a command-line argument: --doubleprec.

force_floata boolean

Use float intensities. Maps to a command-line argument: --floattype.

half_sourcea boolean or a pathlike object or string representing a file

Write source volume mapped to halfway space. Maps to a command-line argument: --halfmov %s.

half_source_xfma boolean or a pathlike object or string representing a file

Write transform from source to halfway space. Maps to a command-line argument: --halfmovlta %s.

half_targa boolean or a pathlike object or string representing a file

Write target volume mapped to halfway space. Maps to a command-line argument: --halfdst %s.

half_targ_xfma boolean or a pathlike object or string representing a file

Write transform from target to halfway space. Maps to a command-line argument: --halfdstlta %s.

half_weightsa boolean or a pathlike object or string representing a file

Write weights volume mapped to halfway space. Maps to a command-line argument: --halfweights %s.

high_iterationsan integer

Max # of times on highest resolution. Maps to a command-line argument: --highit %d.

in_xfm_filea pathlike object or string representing an existing file

Use initial transform on source. Maps to a command-line argument: --transform.

init_orienta boolean

Use moments for initial orient (recommended for stripped brains). Maps to a command-line argument: --initorient.

iteration_thresha float

Stop iterations when below threshold. Maps to a command-line argument: --epsit %.3f.

least_squaresa boolean

Use least squares instead of robust estimator. Maps to a command-line argument: --leastsquares.

mask_sourcea pathlike object or string representing an existing file

Image to mask source volume with. Maps to a command-line argument: --maskmov %s.

mask_targeta pathlike object or string representing an existing file

Image to mask target volume with. Maps to a command-line argument: --maskdst %s.

max_iterationsan integer

Maximum # of times on each resolution. Maps to a command-line argument: --maxit %d.

no_inita boolean

Skip transform init. Maps to a command-line argument: --noinit.

no_multia boolean

Work on highest resolution. Maps to a command-line argument: --nomulti.

out_reg_filea bool or None or a pathlike object or string representing a file

Registration file; either True or filename. Maps to a command-line argument: --lta %s. (Nipype default value: True)

outlier_limita float

Set maximal outlier limit in satit. Maps to a command-line argument: --wlimit %.3f.

registered_filea boolean or a pathlike object or string representing a file

Registered image; either True or filename. Maps to a command-line argument: --warp %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

subsample_threshan integer

Subsample if dimension is above threshold size. Maps to a command-line argument: --subsample %d.

trans_onlya boolean

Find 3 parameter translation only. Maps to a command-line argument: --transonly.

weights_filea boolean or a pathlike object or string representing a file

Weights image to write; either True or filename. Maps to a command-line argument: --weights %s.

write_vo2voxa boolean

Output vox2vox matrix (default is RAS2RAS). Maps to a command-line argument: --vox2vox.

half_sourcea pathlike object or string representing an existing file

Source image mapped to halfway space.

half_source_xfma pathlike object or string representing an existing file

Transform file to map source image to halfway space.

half_targa pathlike object or string representing an existing file

Target image mapped to halfway space.

half_targ_xfma pathlike object or string representing an existing file

Transform file to map target image to halfway space.

half_weightsa pathlike object or string representing an existing file

Weights image mapped to halfway space.

out_reg_filea pathlike object or string representing an existing file

Output registration file.

registered_filea pathlike object or string representing an existing file

Output image with registration applied.

weights_filea pathlike object or string representing an existing file

Image of weights used.

SegmentCC

Link to code

Bases: FSCommand

Wrapped executable: mri_cc.

This program segments the corpus callosum into five separate labels in the subcortical segmentation volume ‘aseg.mgz’. The divisions of the cc are equally spaced in terms of distance along the primary eigendirection (pretty much the long axis) of the cc. The lateral extent can be changed with the -T <thickness> parameter, where <thickness> is the distance off the midline (so -T 1 would result in the who CC being 3mm thick). The default is 2 so it’s 5mm thick. The aseg.stats values should be volume.

Examples

>>> from nipype.interfaces import freesurfer
>>> SegmentCC_node = freesurfer.SegmentCC()
>>> SegmentCC_node.inputs.in_file = "aseg.mgz"
>>> SegmentCC_node.inputs.in_norm = "norm.mgz"
>>> SegmentCC_node.inputs.out_rotation = "cc.lta"
>>> SegmentCC_node.inputs.subject_id = "test"
>>> SegmentCC_node.cmdline
'mri_cc -aseg aseg.mgz -o aseg.auto.mgz -lta cc.lta test'
in_filea pathlike object or string representing an existing file

Input aseg file to read from subjects directory. Maps to a command-line argument: -aseg %s.

in_norma pathlike object or string representing an existing file

Required undocumented input {subject}/mri/norm.mgz.

out_rotationa pathlike object or string representing a file

Global filepath for writing rotation lta. Maps to a command-line argument: -lta %s.

subject_ida string

Subject name. Maps to a command-line argument: %s (position: -1). (Nipype default value: subject_id)

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

copy_inputsa boolean

If running as a node, set this to True.This will copy the input files to the node directory.

environa 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’

Environment variables. (Nipype default value: {})

out_filea pathlike object or string representing a file

Filename to write aseg including CC. Maps to a command-line argument: -o %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing a file

Output segmentation uncluding corpus collosum.

out_rotationa pathlike object or string representing a file

Output lta rotation file.

SegmentCC.aggregate_outputs(runtime=None, needed_outputs=None)

Collate expected outputs and apply output traits validation.

SegmentCC.run(**inputs)

Execute this interface.

This interface will not raise an exception if runtime.returncode is non-zero.

Parameters:
  • cwd (specify a folder where the interface should be run) –

  • inputs (allows the interface settings to be updated) –

Returns:

results – A copy of the instance that was executed, provenance information and, if successful, results

Return type:

nipype.interfaces.base.support.InterfaceResult

SegmentWM

Link to code

Bases: FSCommand

Wrapped executable: mri_segment.

This program segments white matter from the input volume. The input volume should be normalized such that white matter voxels are ~110-valued, and the volume is conformed to 256^3.

Examples

>>> from nipype.interfaces import freesurfer
>>> SegmentWM_node = freesurfer.SegmentWM()
>>> SegmentWM_node.inputs.in_file = "norm.mgz"
>>> SegmentWM_node.inputs.out_file = "wm.seg.mgz"
>>> SegmentWM_node.cmdline
'mri_segment norm.mgz wm.seg.mgz'
in_filea pathlike object or string representing an existing file

Input file for SegmentWM. Maps to a command-line argument: %s (position: -2).

out_filea pathlike object or string representing a file

File to be written as output for SegmentWM. Maps to a command-line argument: %s (position: -1).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing a file

Output white matter segmentation.

Smooth

Link to code

Bases: FSCommand

Wrapped executable: mris_volsmooth.

Use FreeSurfer mris_volsmooth to smooth a volume

This function smoothes cortical regions on a surface and non-cortical regions in volume.

Note

Cortical voxels are mapped to the surface (3D->2D) and then the smoothed values from the surface are put back into the volume to fill the cortical ribbon. If data is smoothed with this algorithm, one has to be careful about how further processing is interpreted.

Examples

>>> from nipype.interfaces.freesurfer import Smooth
>>> smoothvol = Smooth(in_file='functional.nii', smoothed_file = 'foo_out.nii', reg_file='register.dat', surface_fwhm=10, vol_fwhm=6)
>>> smoothvol.cmdline
'mris_volsmooth --i functional.nii --reg register.dat --o foo_out.nii --fwhm 10.000000 --vol-fwhm 6.000000'
in_filea pathlike object or string representing an existing file

Source volume. Maps to a command-line argument: --i %s.

num_itersan integer >= 1

Number of iterations instead of fwhm. Maps to a command-line argument: --niters %d. Mutually exclusive with inputs: surface_fwhm.

reg_filea pathlike object or string representing an existing file

Registers volume to surface anatomical . Maps to a command-line argument: --reg %s.

surface_fwhma floating point number >= 0.0

Surface FWHM in mm. Maps to a command-line argument: --fwhm %f. Mutually exclusive with inputs: num_iters. Requires inputs: reg_file.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

proj_fraca float

Project frac of thickness a long surface normal. Maps to a command-line argument: --projfrac %s. Mutually exclusive with inputs: proj_frac_avg.

proj_frac_avga tuple of the form: (a float, a float, a float)

Average a long normal min max delta. Maps to a command-line argument: --projfrac-avg %.2f %.2f %.2f. Mutually exclusive with inputs: proj_frac.

smoothed_filea pathlike object or string representing a file

Output volume. Maps to a command-line argument: --o %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

vol_fwhma floating point number >= 0.0

Volume smoothing outside of surface. Maps to a command-line argument: --vol-fwhm %f.

smoothed_filea pathlike object or string representing an existing file

Smoothed input volume.

SynthesizeFLASH

Link to code

Bases: FSCommand

Wrapped executable: mri_synthesize.

Synthesize a FLASH acquisition from T1 and proton density maps.

Examples

>>> from nipype.interfaces.freesurfer import SynthesizeFLASH
>>> syn = SynthesizeFLASH(tr=20, te=3, flip_angle=30)
>>> syn.inputs.t1_image = 'T1.mgz'
>>> syn.inputs.pd_image = 'PD.mgz'
>>> syn.inputs.out_file = 'flash_30syn.mgz'
>>> syn.cmdline
'mri_synthesize 20.00 30.00 3.000 T1.mgz PD.mgz flash_30syn.mgz'
flip_anglea float

Flip angle (in degrees). Maps to a command-line argument: %.2f (position: 3).

pd_imagea pathlike object or string representing an existing file

Image of proton density values. Maps to a command-line argument: %s (position: 6).

t1_imagea pathlike object or string representing an existing file

Image of T1 values. Maps to a command-line argument: %s (position: 5).

tea float

Echo time (in msec). Maps to a command-line argument: %.3f (position: 4).

tra float

Repetition time (in msec). Maps to a command-line argument: %.2f (position: 2).

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

environa 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’

Environment variables. (Nipype default value: {})

fixed_weightinga boolean

Use a fixed weighting to generate optimal gray/white contrast. Maps to a command-line argument: -w (position: 1).

out_filea pathlike object or string representing a file

Image to write. Maps to a command-line argument: %s.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

out_filea pathlike object or string representing an existing file

Synthesized FLASH acquisition.

UnpackSDICOMDir

Link to code

Bases: FSCommand

Wrapped executable: unpacksdcmdir.

Use unpacksdcmdir to convert dicom files

Call unpacksdcmdir -help from the command line to see more information on using this command.

Examples

>>> from nipype.interfaces.freesurfer import UnpackSDICOMDir
>>> unpack = UnpackSDICOMDir()
>>> unpack.inputs.source_dir = '.'
>>> unpack.inputs.output_dir = '.'
>>> unpack.inputs.run_info = (5, 'mprage', 'nii', 'struct')
>>> unpack.inputs.dir_structure = 'generic'
>>> unpack.cmdline
'unpacksdcmdir -generic -targ . -run 5 mprage nii struct -src .'
configa pathlike object or string representing an existing file

Specify unpacking rules in file. Maps to a command-line argument: -cfg %s. Mutually exclusive with inputs: run_info, config, seq_config.

run_infoa tuple of the form: (an integer, a string, a string, a string)

Runno subdir format name : spec unpacking rules on cmdline. Maps to a command-line argument: -run %d %s %s %s. Mutually exclusive with inputs: run_info, config, seq_config.

seq_configa pathlike object or string representing an existing file

Specify unpacking rules based on sequence. Maps to a command-line argument: -seqcfg %s. Mutually exclusive with inputs: run_info, config, seq_config.

source_dira pathlike object or string representing an existing directory

Directory with the DICOM files. Maps to a command-line argument: -src %s.

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

dir_structure‘fsfast’ or ‘generic’

Unpack to specified directory structures. Maps to a command-line argument: -%s.

environa 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’

Environment variables. (Nipype default value: {})

log_filea pathlike object or string representing an existing file

Explicitly set log file. Maps to a command-line argument: -log %s.

no_info_dumpa boolean

Do not create infodump file. Maps to a command-line argument: -noinfodump.

no_unpack_erra boolean

Do not try to unpack runs with errors. Maps to a command-line argument: -no-unpackerr.

output_dira pathlike object or string representing a directory

Top directory into which the files will be unpacked. Maps to a command-line argument: -targ %s.

scan_onlya pathlike object or string representing an existing file

Only scan the directory and put result in file. Maps to a command-line argument: -scanonly %s.

spm_zeropadan integer

Set frame number zero padding width for SPM. Maps to a command-line argument: -nspmzeropad %d.

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

WatershedSkullStrip

Link to code

Bases: FSCommand

Wrapped executable: mri_watershed.

This program strips skull and other outer non-brain tissue and produces the brain volume from T1 volume or the scanned volume.

The “watershed” segmentation algorithm was used to determine the intensity values for white matter, grey matter, and CSF. A force field was then used to fit a spherical surface to the brain. The shape of the surface fit was then evaluated against a previously derived template.

The default parameters are: -w 0.82 -b 0.32 -h 10 -seedpt -ta -wta

(Segonne 2004)

Examples

>>> from nipype.interfaces.freesurfer import WatershedSkullStrip
>>> skullstrip = WatershedSkullStrip()
>>> skullstrip.inputs.in_file = "T1.mgz"
>>> skullstrip.inputs.t1 = True
>>> skullstrip.inputs.transform = "transforms/talairach_with_skull.lta"
>>> skullstrip.inputs.out_file = "brainmask.auto.mgz"
>>> skullstrip.cmdline
'mri_watershed -T1 transforms/talairach_with_skull.lta T1.mgz brainmask.auto.mgz'
in_filea pathlike object or string representing an existing file

Input volume. Maps to a command-line argument: %s (position: -2).

out_filea pathlike object or string representing a file

Output volume. Maps to a command-line argument: %s (position: -1). (Nipype default value: brainmask.auto.mgz)

argsa string

Additional parameters to the command. Maps to a command-line argument: %s.

brain_atlasa pathlike object or string representing an existing file

Maps to a command-line argument: -brain_atlas %s (position: -4).

environa 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’

Environment variables. (Nipype default value: {})

subjects_dira pathlike object or string representing an existing directory

Subjects directory.

t1a boolean

Specify T1 input volume (T1 grey value = 110). Maps to a command-line argument: -T1.

transforma pathlike object or string representing a file

Undocumented. Maps to a command-line argument: %s (position: -3).

out_filea pathlike object or string representing a file

Skull stripped brain volume.