Transforms structures with the connected transformix parameters. Existing initial transforms are ignored. NB: See details regarding deformable transforms under Settings - Fixed to Moving.
The transformix parameters to be applied.
Type: TransformixParameter, Required, Single
The structure set which should be transformed.
Type: RTStructCollection, Required, Single
An image reference which specifies at what slice locations the contours should be generated. If a reference is not supplied, the polygon points are still transformed, but the contours may not be coplanar.
Type: Image4DFloat, Optional, Single
The transformed structure set.
Fixed to Moving Boolean
By default this node will transform the structure points from the moving image space to the fixed, set this to perform the transformation from the fixed image space to the moving. NB: This setting will only have effect on linear transforms, i.e. translation, rigid and affine transforms, since the inverse of a deformable registration can only be obtained through an optimization. To perform a moving to fixed deformable structure transform, either first invert the deformation field using the method specified in the elastix manual, or perform the inverse deformable registration.
Deformable Structure Generation
Min Polygon Area (mm2) Number
The minimum polygon area that will be generated after a deformable transform of the structure set. Smaller structures will be disregarded.
Decimate Points Boolean
If set the number of points in the result will be reduced.
Set the maximum number of iterations for polygon reduction.
Stopping Criteria Number
The maximum area the parallelogram can have for a point to be removed in mm2. See Reduce.
Image Type Selection
The type of image to get information from.
Values: Mask, Image, Complex, Vector
1. S. Klein, M. Staring, K. Murphy, M.A. Viergever, J.P.W. Pluim, "elastix: a toolbox for intensity based medical image registration", IEEE Transactions on Medical Imaging, vol. 29, no. 1, pp. 196 - 205, January 2010.
2. D.P. Shamonin, E.E. Bron, B.P.F. Lelieveldt, M. Smits, S. Klein and M. Staring, "Fast Parallel Image Registration on CPU and GPU for Diagnostic Classification of Alzheimer’s Disease", Frontiers in Neuroinformatics, vol. 7, no. 50, pp. 1-15, January 2014.
3. "The Insight Segmentation and Registration Toolkit" www.itk.org
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