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# nipype.interfaces.ants.legacy module

ANTS Legacy Interfaces

These interfaces are for programs that have been deprecated by ANTs, but are preserved for backwards compatibility.

## GenWarpFields

Link to code

> Bases: antsIntroduction

> Wrapped executable: `antsIntroduction.sh`.

> input_imagea pathlike object or string representing an existing file

>   Input image to warp to template. Maps to a command-line argument: `-i %s`.

> reference_imagea pathlike object or string representing an existing file

>   Template file to warp to. Maps to a command-line argument: `-r %s`.

> argsa string

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

> bias_field_correctiona boolean

>   Applies bias field correction to moving image. Maps to a command-line argument: `-n 1`.

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `-d %d` (position: 1). (Nipype default value: `3`)

> 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: `{}`)

> force_proceeda boolean

>   Force script to proceed even if headers may be incompatible. Maps to a command-line argument: `-f 1`.

> inverse_warp_template_labelsa boolean

>   Applies inverse warp to the template labels to estimate label positions in target space (use for template-based segmentation). Maps to a command-line argument: `-l`.

> max_iterationsa 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 iterations, L = fine resolution iterations. Maps to a command-line argument: `-m %s`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> out_prefixa string

>   Prefix that is prepended to all output files (default = ants_). Maps to a command-line argument: `-o %s`. (Nipype default value: `ants_`)

> quality_checka boolean

>   Perform a quality check of the result. Maps to a command-line argument: `-q 1`.

> 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). Maps to a command-line argument: `-s %s`.

> transformation_model‘GR’ or ‘EL’ or ‘SY’ or ‘S2’ or ‘EX’ or ‘DD’ or ‘RI’ or ‘RA’

>   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. Maps to a command-line argument: `-t %s`. (Nipype default value: `GR`)

> affine_transformationa pathlike object or string representing an existing file

>   Affine (prefix_Affine.txt).

> input_filea pathlike object or string representing an existing file

>   Input image (prefix_repaired.nii).

> inverse_warp_fielda pathlike object or string representing an existing file

>   Inverse warp field (prefix_InverseWarp.nii).

> output_filea pathlike object or string representing an existing file

>   Output image (prefix_deformed.nii).

> warp_fielda pathlike object or string representing an existing file

>   Warp field (prefix_Warp.nii).

## antsIntroduction

Link to code

> Bases: ANTSCommand

> Wrapped executable: `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'

> input_imagea pathlike object or string representing an existing file

>   Input image to warp to template. Maps to a command-line argument: `-i %s`.

> reference_imagea pathlike object or string representing an existing file

>   Template file to warp to. Maps to a command-line argument: `-r %s`.

> argsa string

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

> bias_field_correctiona boolean

>   Applies bias field correction to moving image. Maps to a command-line argument: `-n 1`.

> dimension3 or 2

>   Image dimension (2 or 3). Maps to a command-line argument: `-d %d` (position: 1). (Nipype default value: `3`)

> 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: `{}`)

> force_proceeda boolean

>   Force script to proceed even if headers may be incompatible. Maps to a command-line argument: `-f 1`.

> inverse_warp_template_labelsa boolean

>   Applies inverse warp to the template labels to estimate label positions in target space (use for template-based segmentation). Maps to a command-line argument: `-l`.

> max_iterationsa 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 iterations, L = fine resolution iterations. Maps to a command-line argument: `-m %s`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> out_prefixa string

>   Prefix that is prepended to all output files (default = ants_). Maps to a command-line argument: `-o %s`. (Nipype default value: `ants_`)

> quality_checka boolean

>   Perform a quality check of the result. Maps to a command-line argument: `-q 1`.

> 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). Maps to a command-line argument: `-s %s`.

> transformation_model‘GR’ or ‘EL’ or ‘SY’ or ‘S2’ or ‘EX’ or ‘DD’ or ‘RI’ or ‘RA’

>   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. Maps to a command-line argument: `-t %s`. (Nipype default value: `GR`)

> affine_transformationa pathlike object or string representing an existing file

>   Affine (prefix_Affine.txt).

> input_filea pathlike object or string representing an existing file

>   Input image (prefix_repaired.nii).

> inverse_warp_fielda pathlike object or string representing an existing file

>   Inverse warp field (prefix_InverseWarp.nii).

> output_filea pathlike object or string representing an existing file

>   Output image (prefix_deformed.nii).

> warp_fielda pathlike object or string representing an existing file

>   Warp field (prefix_Warp.nii).

## buildtemplateparallel

Link to code

> Bases: ANTSCommand

> Wrapped executable: `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'

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

>   List of images to generate template from. Maps to a command-line argument: `%s` (position: -1).

> argsa string

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

> bias_field_correctiona boolean

>   Applies bias field correction to moving image. Maps to a command-line argument: `-n 1`.

> dimension3 or 2 or 4

>   Image dimension (2, 3 or 4). Maps to a command-line argument: `-d %d` (position: 1). (Nipype default value: `3`)

> 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: `{}`)

> gradient_step_sizea float

>   Smaller magnitude results in more cautious steps (default = .25). Maps to a command-line argument: `-g %f`.

> iteration_limitan integer

>   Iterations of template construction. Maps to a command-line argument: `-i %d`. (Nipype default value: `4`)

> max_iterationsa 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 iterations, L = fine resolution iterations. Maps to a command-line argument: `-m %s`.

> num_coresan integer

>   Requires parallelization = 2 (PEXEC). Sets number of cpu cores to use. Maps to a command-line argument: `-j %d`. Requires inputs: `parallelization`.

> num_threadsan integer

>   Number of ITK threads to use. (Nipype default value: `1`)

> out_prefixa string

>   Prefix that is prepended to all output files (default = antsTMPL_). Maps to a command-line argument: `-o %s`. (Nipype default value: `antsTMPL_`)

> parallelization0 or 1 or 2

>   Control for parallel processing (0 = serial, 1 = use PBS, 2 = use PEXEC, 3 = use Apple XGrid. Maps to a command-line argument: `-c %d`. (Nipype default value: `0`)

> rigid_body_registrationa boolean

>   Registers inputs before creating template (useful if no initial template available). Maps to a command-line argument: `-r 1`.

> 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). Maps to a command-line argument: `-s %s`.

> transformation_model‘GR’ or ‘EL’ or ‘SY’ or ‘S2’ or ‘EX’ or ‘DD’

>   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. Maps to a command-line argument: `-t %s`. (Nipype default value: `GR`)

> use_first_as_targeta boolean

>   Uses first volume as target of all inputs. When not used, an unbiased average image is used to start.

> final_template_filea pathlike object or string representing an existing file

>   Final ANTS template.

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

>   Outputs for each input image. Includes warp field, inverse warp, Affine, original image (repaired) and warped image (deformed).

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

>   Templates from different stages of iteration.