nipype.interfaces.freesurfer.longitudinal module

Provides interfaces to various longitudinal commands provided by freesurfer

FuseSegmentations

Link to code

Bases: FSCommand

Wrapped executable: mri_fuse_segmentations.

fuse segmentations together from multiple timepoints

Examples

>>> from nipype.interfaces.freesurfer import FuseSegmentations
>>> fuse = FuseSegmentations()
>>> fuse.inputs.subject_id = 'tp.long.A.template'
>>> fuse.inputs.timepoints = ['tp1', 'tp2']
>>> fuse.inputs.out_file = 'aseg.fused.mgz'
>>> fuse.inputs.in_segmentations = ['aseg.mgz', 'aseg.mgz']
>>> fuse.inputs.in_segmentations_noCC = ['aseg.mgz', 'aseg.mgz']
>>> fuse.inputs.in_norms = ['norm.mgz', 'norm.mgz', 'norm.mgz']
>>> fuse.cmdline
'mri_fuse_segmentations -n norm.mgz -a aseg.mgz -c aseg.mgz tp.long.A.template tp1 tp2'

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

-n <filename>

name of norm file to use (default: norm.mgs) must include the corresponding norm file for all given timepoints as well as for the current subject.

Maps to a command-line argument: -n %s.

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

Name of aseg file to use (default: aseg.mgz) must include the aseg files for all the given timepoints. Maps to a command-line argument: -a %s.

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

Name of aseg file w/o CC labels (default: aseg.auto_noCCseg.mgz) must include the corresponding file for all the given timepoints. Maps to a command-line argument: -c %s.

out_file : a pathlike object or string representing a file

Output fused segmentation file.

timepoints : a list of items which are a string

Subject_ids or timepoints to be processed. Maps to a command-line argument: %s (position: -2).

args : a unicode string

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

environ : a dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

Environment variables. (Nipype default value: {})

subject_id : a string

Subject_id being processed. Maps to a command-line argument: %s (position: -3).

subjects_dir : a pathlike object or string representing an existing directory

Subjects directory.

out_file : a pathlike object or string representing a file

Output fused segmentation file.

RobustTemplate

Link to code

Bases: FSCommandOpenMP

Wrapped executable: mri_robust_template.

construct an unbiased robust template for longitudinal volumes

Examples

>>> from nipype.interfaces.freesurfer import RobustTemplate
>>> template = RobustTemplate()
>>> template.inputs.in_files = ['structural.nii', 'functional.nii']
>>> template.inputs.auto_detect_sensitivity = True
>>> template.inputs.average_metric = 'mean'
>>> template.inputs.initial_timepoint = 1
>>> template.inputs.fixed_timepoint = True
>>> template.inputs.no_iteration = True
>>> template.inputs.subsample_threshold = 200
>>> template.cmdline  #doctest:
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template mri_robust_template_out.mgz --subsample 200'
>>> template.inputs.out_file = 'T1.nii'
>>> template.cmdline  #doctest:
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --subsample 200'

>>> template.inputs.transform_outputs = ['structural.lta',
...                                      'functional.lta']
>>> template.inputs.scaled_intensity_outputs = ['structural-iscale.txt',
...                                             'functional-iscale.txt']
>>> template.cmdline    #doctest: +ELLIPSIS
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --iscaleout .../structural-iscale.txt .../functional-iscale.txt --subsample 200 --lta .../structural.lta .../functional.lta'

>>> template.inputs.transform_outputs = True
>>> template.inputs.scaled_intensity_outputs = True
>>> template.cmdline    #doctest: +ELLIPSIS
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --iscaleout .../is1.txt .../is2.txt --subsample 200 --lta .../tp1.lta .../tp2.lta'

>>> template.run()  #doctest: +SKIP

References

[https://surfer.nmr.mgh.harvard.edu/fswiki/mri_robust_template]

auto_detect_sensitivity : a boolean

Auto-detect good sensitivity (recommended for head or full brain scans). Maps to a command-line argument: --satit. Mutually exclusive with inputs: outlier_sensitivity.

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

Input movable volumes to be aligned to common mean/median template. Maps to a command-line argument: --mov %s.

out_file : a pathlike object or string representing a file

Output template volume (final mean/median image). Maps to a command-line argument: --template %s. (Nipype default value: mri_robust_template_out.mgz)

outlier_sensitivity : a float

Set outlier sensitivity manually (e.g. “–sat 4.685” ). Higher values mean less sensitivity. Maps to a command-line argument: --sat %.4f. Mutually exclusive with inputs: auto_detect_sensitivity.

args : a unicode string

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

average_metric : ‘median’ or ‘mean’

Construct template from: 0 Mean, 1 Median (default). Maps to a command-line argument: --average %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’

Environment variables. (Nipype default value: {})

fixed_timepoint : a boolean

Map everthing to init TP# (init TP is not resampled). Maps to a command-line argument: --fixtp.

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

Use initial intensity scales. Maps to a command-line argument: --iscalein %s.

initial_timepoint : an integer (int or long)

Use TP# for spacial init (default random), 0: no init. Maps to a command-line argument: --inittp %d.

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

Use initial transforms (lta) on source. Maps to a command-line argument: --ixforms %s.

intensity_scaling : a boolean

Allow also intensity scaling (default off). Maps to a command-line argument: --iscale.

no_iteration : a boolean

Do not iterate, just create first template. Maps to a command-line argument: --noit.

num_threads : an integer (int or long)

Allows for specifying more threads.

scaled_intensity_outputs : a list of items which are a pathlike object or string representing a file or a boolean

Final intensity scales (will activate –iscale). Maps to a command-line argument: --iscaleout %s.

subjects_dir : a pathlike object or string representing an existing directory

Subjects directory.

subsample_threshold : an integer (int or long)

Subsample if dim > # on all axes (default no subs.). Maps to a command-line argument: --subsample %d.

transform_outputs : a list of items which are a pathlike object or string representing a file or a boolean

Output xforms to template (for each input). Maps to a command-line argument: --lta %s.

out_file : a pathlike object or string representing an existing file

Output template volume (final mean/median image).

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

Output final intensity scales.

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

Output xform files from moving to template.