Registration¶
- CPAC.registration.create_bbregister_func_to_anat(phase_diff_distcor=False, name='bbregister_func_to_anat')[source]¶
Registers a functional scan in native space to structural. This is meant to be used after create_nonlinear_register() has been run and relies on some of it’s outputs.
- Parameters:
- fieldmap_distortionbool, optional
If field map-based distortion correction is being run, FLIRT should take in the appropriate field map-related inputs.
- namestring, optional
Name of the workflow.
- Returns:
- register_func_to_anatnipype.pipeline.engine.Workflow
Notes
Workflow Inputs:
inputspec.func : string (nifti file) Input functional scan to be registered to MNI space inputspec.anat : string (nifti file) Corresponding full-head or brain scan of subject inputspec.linear_reg_matrix : string (mat file) Affine matrix from linear functional to anatomical registration inputspec.anat_wm_segmentation : string (nifti file) White matter segmentation probability mask in anatomical space inputspec.bbr_schedule : string (.sch file) Boundary based registration schedule file for flirt command
Workflow Outputs:
outputspec.func_to_anat_linear_xfm : string (mat file) Affine transformation from functional to anatomical native space outputspec.anat_func : string (nifti file) Functional data in anatomical space
- CPAC.registration.create_fsl_fnirt_nonlinear_reg(name='fsl_fnirt_nonlinear_reg')[source]¶
Performs non-linear registration of an input file to a reference file using FSL FNIRT.
- Parameters:
- namestring, optional
Name of the workflow.
- Returns:
- nonlinear_registernipype.pipeline.engine.Workflow
Notes
Workflow Inputs:
inputspec.input_skull : string (nifti file) File of input brain with skull inputspec.reference_skull : string (nifti file) Target brain with skull to normalize to inputspec.fnirt_config : string (fsl fnirt config file) Configuration file containing parameters that can be specified in fnirt
Workflow Outputs:
outputspec.output_brain : string (nifti file) Normalizion of input brain file outputspec.nonlinear_xfm : string Nonlinear field coefficients file of nonlinear transformation
Registration Procedure:
Perform a nonlinear registration on an input file to the reference file utilizing affine transformation from the previous step as a starting point.
Invert the affine transformation to provide the user a transformation (affine only) from the space of the reference file to the input file.
Workflow Graph:
Detailed Workflow Graph: .. image:: ../images/nonlinear_register_detailed.dot.png
- width:
500
- CPAC.registration.create_fsl_fnirt_nonlinear_reg_nhp(name='fsl_fnirt_nonlinear_reg_nhp')[source]¶
Performs non-linear registration of an input file to a reference file using FSL FNIRT.
- Parameters:
- namestring, optional
Name of the workflow.
- Returns:
- nonlinear_registernipype.pipeline.engine.Workflow
Notes
Workflow Inputs:
inputspec.input_skull : string (nifti file) File of input brain with skull inputspec.reference_skull : string (nifti file) Target brain with skull to normalize to inputspec.fnirt_config : string (fsl fnirt config file) Configuration file containing parameters that can be specified in fnirt
Workflow Outputs:
outputspec.output_brain : string (nifti file) Normalizion of input brain file outputspec.nonlinear_xfm : string Nonlinear field coefficients file of nonlinear transformation outputspec.nonlinear_warp : string Nonlinear output file with warp field
Registration Procedure:
Perform a nonlinear registration on an input file to the reference file utilizing affine transformation from the previous step as a starting point.
Invert the affine transformation to provide the user a transformation (affine only) from the space of the reference file to the input file.
Workflow Graph:
Detailed Workflow Graph: .. image:: ../images/nonlinear_register_detailed.dot.png
- width:
500
- CPAC.registration.create_register_func_to_anat(config, phase_diff_distcor=False, name='register_func_to_anat')[source]¶
Registers a functional scan in native space to anatomical space using a linear transform and does not include bbregister.
- Parameters:
- configconfiguration, mandatory
Pipeline configuration.
- fieldmap_distortionbool, optional
If field map-based distortion correction is being run, FLIRT should take in the appropriate field map-related inputs.
- namestring, optional
Name of the workflow.
- Returns:
- create_register_func_to_anatnipype.pipeline.engine.Workflow
Notes
Workflow Inputs:
inputspec.func : string (nifti file) Input functional scan to be registered to anatomical space inputspec.anat : string (nifti file) Corresponding anatomical scan of subject inputspec.interp : string Type of interpolation to use ('trilinear' or 'nearestneighbour' or 'sinc')
Workflow Outputs:
outputspec.func_to_anat_linear_xfm_nobbreg : string (mat file) Affine transformation from functional to anatomical native space outputspec.anat_func_nobbreg : string (nifti file) Functional scan registered to anatomical space
- CPAC.registration.create_register_func_to_anat_use_T2(config, name='register_func_to_anat_use_T2')[source]¶
Registers a functional scan in native space to anatomical space using a linear transform and does not include bbregister, use T1 and T2 image.
- Parameters:
- configconfiguration, mandatory
Pipeline configuration.
- namestring, optional
Name of the workflow.
- Returns:
- create_register_func_to_anat_use_T2nipype.pipeline.engine.Workflow
Notes
Workflow Inputs:
inputspec.func : string (nifti file) Input functional scan to be registered to anatomical space inputspec.anat : string (nifti file) Corresponding anatomical scan of subject
Workflow Outputs:
outputspec.func_to_anat_linear_xfm_nobbreg : string (mat file) Affine transformation from functional to anatomical native space outputspec.anat_func_nobbreg : string (nifti file) Functional scan registered to anatomical space
- CPAC.registration.create_wf_calculate_ants_warp(name='create_wf_calculate_ants_warp', num_threads=1, reg_ants_skull=1)[source]¶
Calculates the nonlinear ANTS registration transform. This workflow employs the antsRegistration tool:
- Parameters:
- namestring, optional
Name of the workflow.
- Returns:
- calc_ants_warp_wfnipype.pipeline.engine.Workflow
Notes
Some of the inputs listed below are lists or lists of lists. This is because antsRegistration can perform multiple stages of calculations depending on how the user configures their registration.
For example, if one wants to employ a different metric (with different parameters) at each stage, the lists would be configured like this:
warp_wf.inputs.inputspec.transforms = [‘Rigid’,’Affine’,’SyN’] warp_wf.inputs.inputspec.transform_parameters = [[0.1],[0.1],[0.1,3,0]]
..where each element in the first list is a metric to be used at each stage, ‘Rigid’ being for stage 1, ‘Affine’ for stage 2, etc. The lists within the list for transform_parameters would then correspond to each stage’s metric, with [0.1] applying to ‘Rigid’ and ‘Affine’ (stages 1 and 2), and [0.1,3,0] applying to ‘SyN’ of stage 3.
In some cases, when a parameter is not needed for a stage, ‘None’ must be entered in its place if there are other parameters for other stages.
Workflow Inputs:
inputspec.moving_brain : string (nifti file) File of brain to be normalized (registered) inputspec.reference_brain : string (nifti file) Target brain file to normalize to inputspec.dimension : integer Dimension of the image (default: 3) inputspec.use_histogram_matching : boolean Histogram match the images before registration inputspec.winsorize_lower_quantile : float Winsorize data based on quantiles (lower range) inputspec.winsorize_higher_quantile : float Winsorize data based on quantiles (higher range) inputspec.metric : list of strings Image metric(s) to be used at each stage inputspec.metric_weight : list of floats Modulate the per-stage weighting of the corresponding metric inputspec.radius_or_number_of_bins : list of integers Number of bins in each stage for the MI and Mattes metric, the radius for other metrics inputspec.sampling_strategy : list of strings Sampling strategy (or strategies) to use for the metrics {None, Regular, or Random} inputspec.sampling_percentage : list of floats Defines the sampling strategy {float value, or None} inputspec.number_of_iterations : list of lists of integers Determines the convergence inputspec.convergence_threshold : list of floats Threshold compared to the slope of the line fitted in convergence inputspec.convergence_window_size : list of integers Window size of convergence calculations inputspec.transforms : list of strings Selection of transform options. See antsRegistration documentation for a full list of options and their descriptions inputspec.transform_parameters : list of lists of floats Fine-tuning for the different transform options inputspec.shrink_factors : list of lists of integers Specify the shrink factor for the virtual domain (typically the fixed image) at each level inputspec.smoothing_sigmas : list of lists of floats Specify the sigma of gaussian smoothing at each level inputspec.fixed_image_mask: (an existing file name) Mask used to limit metric sampling region of the fixed imagein all stages inputspec.interp : string Type of interpolation to use ('Linear' or 'BSpline' or 'LanczosWindowedSinc')
Workflow Outputs:
outputspec.warp_field : string (nifti file) Output warp field of registration outputspec.inverse_warp_field : string (nifti file) Inverse of the warp field of the registration outputspec.ants_affine_xfm : string (.mat file) The affine matrix of the registration outputspec.ants_inverse_affine_xfm : string (.mat file) The affine matrix of the reverse registration outputspec.composite_transform : string (nifti file) The combined transform including the warp field and rigid & affine linear warps outputspec.normalized_output_brain : string (nifti file) Template-registered version of input brain
Registration Procedure:
Calculates a nonlinear anatomical-to-template registration.
Workflow Graph: .. image:
:width: 500
Detailed Workflow Graph: