.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.slicer.filtering.denoising
=====================================


.. _nipype.interfaces.slicer.filtering.denoising.CurvatureAnisotropicDiffusion:


.. index:: CurvatureAnisotropicDiffusion

CurvatureAnisotropicDiffusion
-----------------------------

Code: http://github.com/nipy/nipype/blob/master/nipype/interfaces/slicer/filtering/denoising.py#L21

Wraps command ** CurvatureAnisotropicDiffusion **

title: Curvature Anisotropic Diffusion

category: Filtering.Denoising

description:
Performs anisotropic diffusion on an image using a modified curvature diffusion equation (MCDE).

MCDE does not exhibit the edge enhancing properties of classic anisotropic diffusion, which can under certain conditions undergo a 'negative' diffusion, which enhances the contrast of edges.  Equations of the form of MCDE always undergo positive diffusion, with the conductance term only varying the strength of that diffusion.

 Qualitatively, MCDE compares well with other non-linear diffusion techniques.  It is less sensitive to contrast than classic Perona-Malik style diffusion, and preserves finer detailed structures in images.  There is a potential speed trade-off for using this function in place of Gradient Anisotropic Diffusion.  Each iteration of the solution takes roughly twice as long.  Fewer iterations, however, may be required to reach an acceptable solution.


version: 0.1.0.$Revision: 18864 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.0/Modules/CurvatureAnisotropicDiffusion

contributor: Bill Lorensen

acknowledgements: This command module was derived from Insight/Examples (copyright) Insight Software Consortium

Inputs::

        [Mandatory]

        [Optional]
        args: (a string)
                Additional parameters to the command
        conductance: (a float)
                Conductance controls the sensitivity of the conductance term. As a general rule, the
                lower the value, the more strongly the filter preserves edges. A high value will cause
                diffusion (smoothing) across edges. Note that the number of iterations controls how much
                smoothing is done within regions bounded by edges.
        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
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        inputVolume: (an existing file name)
                Input volume to be filtered
        iterations: (an integer)
                The more iterations, the more smoothing. Each iteration takes the same amount of time.
                If it takes 10 seconds for one iteration, then it will take 100 seconds for 10
                iterations. Note that the conductance controls how much each iteration smooths across
                edges.
        outputVolume: (a boolean or a file name)
                Output filtered
        timeStep: (a float)
                The time step depends on the dimensionality of the image. In Slicer the images are 3D
                and the default (.0625) time step will provide a stable solution.

Outputs::

        outputVolume: (an existing file name)
                Output filtered
