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# nipype.interfaces.slicer.filtering.denoising module

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## CurvatureAnisotropicDiffusion

Link to code

> Bases: SEMLikeCommandLine

> Wrapped executable: `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: 19608 $(alpha)

> documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/CurvatureAnisotropicDiffusion

> contributor: Bill Lorensen (GE)

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

> argsa unicode string

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

> conductancea 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. Maps to a command-line argument: `--conductance %f`.

> 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: `{}`)

> inputVolumea pathlike object or string representing an existing file

>   Input volume to be filtered. Maps to a command-line argument: `%s` (position: -2).

> iterationsan integer (int or long)

>   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. Maps to a command-line argument: `--iterations %d`.

> outputVolumea boolean or a pathlike object or string representing a file

>   Output filtered. Maps to a command-line argument: `%s` (position: -1).

> timeStepa 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. Maps to a command-line argument: `--timeStep %f`.

> outputVolumea pathlike object or string representing an existing file

>   Output filtered.

## GaussianBlurImageFilter

Link to code

> Bases: SEMLikeCommandLine

> Wrapped executable: `GaussianBlurImageFilter`.

> title: Gaussian Blur Image Filter

> category: Filtering.Denoising

> description: Apply a gaussian blurr to an image

> version: 0.1.0.$Revision: 1.1 $(alpha)

> documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/GaussianBlurImageFilter

> contributor: Julien Jomier (Kitware), Stephen Aylward (Kitware)

> acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

> argsa unicode string

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

> 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: `{}`)

> inputVolumea pathlike object or string representing an existing file

>   Input volume. Maps to a command-line argument: `%s` (position: -2).

> outputVolumea boolean or a pathlike object or string representing a file

>   Blurred Volume. Maps to a command-line argument: `%s` (position: -1).

> sigmaa float

>   Sigma value in physical units (e.g., mm) of the Gaussian kernel. Maps to a command-line argument: `--sigma %f`.

> outputVolumea pathlike object or string representing an existing file

>   Blurred Volume.

## GradientAnisotropicDiffusion

Link to code

> Bases: SEMLikeCommandLine

> Wrapped executable: `GradientAnisotropicDiffusion`.

> title: Gradient Anisotropic Diffusion

> category: Filtering.Denoising

> description: Runs gradient anisotropic diffusion on a volume.

> Anisotropic diffusion methods reduce noise (or unwanted detail) in images while preserving specific image features, like edges. For many applications, there is an assumption that light-dark transitions (edges) are interesting. Standard isotropic diffusion methods move and blur light-dark boundaries. Anisotropic diffusion methods are formulated to specifically preserve edges. The conductance term for this implementation is a function of the gradient magnitude of the image at each point, reducing the strength of diffusion at edges. The numerical implementation of this equation is similar to that described in the Perona-Malik paper, but uses a more robust technique for gradient magnitude estimation and has been generalized to N-dimensions.

> version: 0.1.0.$Revision: 19608 $(alpha)

> documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/GradientAnisotropicDiffusion

> contributor: Bill Lorensen (GE)

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

> argsa unicode string

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

> conductancea 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. Maps to a command-line argument: `--conductance %f`.

> 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: `{}`)

> inputVolumea pathlike object or string representing an existing file

>   Input volume to be filtered. Maps to a command-line argument: `%s` (position: -2).

> iterationsan integer (int or long)

>   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. Maps to a command-line argument: `--iterations %d`.

> outputVolumea boolean or a pathlike object or string representing a file

>   Output filtered. Maps to a command-line argument: `%s` (position: -1).

> timeStepa 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. Maps to a command-line argument: `--timeStep %f`.

> outputVolumea pathlike object or string representing an existing file

>   Output filtered.

## MedianImageFilter

Link to code

> Bases: SEMLikeCommandLine

> Wrapped executable: `MedianImageFilter`.

> title: Median Image Filter

> category: Filtering.Denoising

> description: The MedianImageFilter is commonly used as a robust approach for noise reduction. This filter is particularly efficient against “salt-and-pepper” noise. In other words, it is robust to the presence of gray-level outliers. MedianImageFilter computes the value of each output pixel as the statistical median of the neighborhood of values around the corresponding input pixel.

> version: 0.1.0.$Revision: 19608 $(alpha)

> documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/MedianImageFilter

> contributor: Bill Lorensen (GE)

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

> argsa unicode string

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

> 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: `{}`)

> inputVolumea pathlike object or string representing an existing file

>   Input volume to be filtered. Maps to a command-line argument: `%s` (position: -2).

> neighborhooda list of items which are an integer (int or long)

>   The size of the neighborhood in each dimension. Maps to a command-line argument: `--neighborhood %s`.

> outputVolumea boolean or a pathlike object or string representing a file

>   Output filtered. Maps to a command-line argument: `%s` (position: -1).

> outputVolumea pathlike object or string representing an existing file

>   Output filtered.