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# interfaces.ants.legacy

## GenWarpFields

Link to code

Wraps command antsIntroduction.sh

Inputs:

    [Mandatory]
    input_image: (an existing file name)
            input image to warp to template
    reference_image: (an existing file name)
            template file to warp to

    [Optional]
    args: (a string)
            Additional parameters to the command
    bias_field_correction: (a boolean)
            Applies bias field correction to moving image
    dimension: (3 or 2, nipype default value: 3)
            image dimension (2 or 3)
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    force_proceed: (a boolean)
            force script to proceed even if headers may be incompatible
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    inverse_warp_template_labels: (a boolean)
            Applies inverse warp to the template labels to estimate label positions in target space
            (use for template-based segmentation)
    max_iterations: (a list of items which are an integer)
            maximum number of iterations (must be list of integers in the form [J,K,L...]: J =
            coarsest resolution iterations, K = middle resolution interations, L = fine resolution
            iterations
    num_threads: (an integer, nipype default value: -1)
            Number of ITK threads to use
    out_prefix: (a string, nipype default value: ants_)
            Prefix that is prepended to all output files (default = ants_)
    quality_check: (a boolean)
            Perform a quality check of the result
    similarity_metric: ('PR' or 'CC' or 'MI' or 'MSQ')
            Type of similartiy metric used for registration (CC = cross correlation, MI = mutual
            information, PR = probability mapping, MSQ = mean square difference)
    transformation_model: ('GR' or 'EL' or 'SY' or 'S2' or 'EX' or 'DD' or 'RI' or 'RA',
             nipype default value: GR)
            Type of transofmration model used for registration (EL = elastic transformation model,
            SY = SyN with time, arbitrary number of time points, S2 =  SyN with time optimized for 2
            time points, GR = greedy SyN, EX = exponential, DD = diffeomorphic demons style
            exponential mapping, RI = purely rigid, RA = affine rigid

Outputs:

    affine_transformation: (an existing file name)
            affine (prefix_Affine.txt)
    input_file: (an existing file name)
            input image (prefix_repaired.nii)
    inverse_warp_field: (an existing file name)
            inverse warp field (prefix_InverseWarp.nii)
    output_file: (an existing file name)
            output image (prefix_deformed.nii)
    warp_field: (an existing file name)
            warp field (prefix_Warp.nii)

## antsIntroduction

Link to code

Wraps command antsIntroduction.sh

Uses ANTS to generate matrices to warp data from one space to another.

### Examples

    >>> from nipype.interfaces.ants.legacy import antsIntroduction
    >>> warp = antsIntroduction()
    >>> warp.inputs.reference_image = 'Template_6.nii'
    >>> warp.inputs.input_image = 'structural.nii'
    >>> warp.inputs.max_iterations = [30,90,20]
    >>> warp.cmdline
    'antsIntroduction.sh -d 3 -i structural.nii -m 30x90x20 -o ants_ -r Template_6.nii -t GR'

Inputs:

    [Mandatory]
    input_image: (an existing file name)
            input image to warp to template
    reference_image: (an existing file name)
            template file to warp to

    [Optional]
    args: (a string)
            Additional parameters to the command
    bias_field_correction: (a boolean)
            Applies bias field correction to moving image
    dimension: (3 or 2, nipype default value: 3)
            image dimension (2 or 3)
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    force_proceed: (a boolean)
            force script to proceed even if headers may be incompatible
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    inverse_warp_template_labels: (a boolean)
            Applies inverse warp to the template labels to estimate label positions in target space
            (use for template-based segmentation)
    max_iterations: (a list of items which are an integer)
            maximum number of iterations (must be list of integers in the form [J,K,L...]: J =
            coarsest resolution iterations, K = middle resolution interations, L = fine resolution
            iterations
    num_threads: (an integer, nipype default value: -1)
            Number of ITK threads to use
    out_prefix: (a string, nipype default value: ants_)
            Prefix that is prepended to all output files (default = ants_)
    quality_check: (a boolean)
            Perform a quality check of the result
    similarity_metric: ('PR' or 'CC' or 'MI' or 'MSQ')
            Type of similartiy metric used for registration (CC = cross correlation, MI = mutual
            information, PR = probability mapping, MSQ = mean square difference)
    transformation_model: ('GR' or 'EL' or 'SY' or 'S2' or 'EX' or 'DD' or 'RI' or 'RA',
             nipype default value: GR)
            Type of transofmration model used for registration (EL = elastic transformation model,
            SY = SyN with time, arbitrary number of time points, S2 =  SyN with time optimized for 2
            time points, GR = greedy SyN, EX = exponential, DD = diffeomorphic demons style
            exponential mapping, RI = purely rigid, RA = affine rigid

Outputs:

    affine_transformation: (an existing file name)
            affine (prefix_Affine.txt)
    input_file: (an existing file name)
            input image (prefix_repaired.nii)
    inverse_warp_field: (an existing file name)
            inverse warp field (prefix_InverseWarp.nii)
    output_file: (an existing file name)
            output image (prefix_deformed.nii)
    warp_field: (an existing file name)
            warp field (prefix_Warp.nii)

## buildtemplateparallel

Link to code

Wraps command buildtemplateparallel.sh

Generate a optimal average template

Warning

This can take a VERY long time to complete

### Examples

    >>> from nipype.interfaces.ants.legacy import buildtemplateparallel
    >>> tmpl = buildtemplateparallel()
    >>> tmpl.inputs.in_files = ['T1.nii', 'structural.nii']
    >>> tmpl.inputs.max_iterations = [30, 90, 20]
    >>> tmpl.cmdline
    'buildtemplateparallel.sh -d 3 -i 4 -m 30x90x20 -o antsTMPL_ -c 0 -t GR T1.nii structural.nii'

Inputs:

    [Mandatory]
    in_files: (a list of items which are an existing file name)
            list of images to generate template from

    [Optional]
    args: (a string)
            Additional parameters to the command
    bias_field_correction: (a boolean)
            Applies bias field correction to moving image
    dimension: (3 or 2, nipype default value: 3)
            image dimension (2 or 3)
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    gradient_step_size: (a float)
            smaller magnitude results in more cautious steps (default = .25)
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    iteration_limit: (an integer, nipype default value: 4)
            iterations of template construction
    max_iterations: (a list of items which are an integer)
            maximum number of iterations (must be list of integers in the form [J,K,L...]: J =
            coarsest resolution iterations, K = middle resolution interations, L = fine resolution
            iterations
    num_cores: (an integer)
            Requires parallelization = 2 (PEXEC). Sets number of cpu cores to use
            requires: parallelization
    num_threads: (an integer, nipype default value: -1)
            Number of ITK threads to use
    out_prefix: (a string, nipype default value: antsTMPL_)
            Prefix that is prepended to all output files (default = antsTMPL_)
    parallelization: (0 or 1 or 2, nipype default value: 0)
            control for parallel processing (0 = serial, 1 = use PBS, 2 = use PEXEC, 3 = use Apple
            XGrid
    rigid_body_registration: (a boolean)
            registers inputs before creating template (useful if no initial template available)
    similarity_metric: ('PR' or 'CC' or 'MI' or 'MSQ')
            Type of similartiy metric used for registration (CC = cross correlation, MI = mutual
            information, PR = probability mapping, MSQ = mean square difference)
    transformation_model: ('GR' or 'EL' or 'SY' or 'S2' or 'EX' or 'DD', nipype default
             value: GR)
            Type of transofmration model used for registration (EL = elastic transformation model,
            SY = SyN with time, arbitrary number of time points, S2 =  SyN with time optimized for 2
            time points, GR = greedy SyN, EX = exponential, DD = diffeomorphic demons style
            exponential mapping
    use_first_as_target: (a boolean)
            uses first volume as target of all inputs. When not used, an unbiased average image is
            used to start.

Outputs:

    final_template_file: (an existing file name)
            final ANTS template
    subject_outfiles: (an existing file name)
            Outputs for each input image. Includes warp field, inverse warp, Affine, original image
            (repaired) and warped image (deformed)
    template_files: (an existing file name)
            Templates from different stages of iteration