[ITK-users] extracting each component of the GradientRecursiveGaussianImageFilter

[michkapopoff at gmail.com]

Hi

I wrote two examples for this filter some time ago:

http://itk.org/ITKExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussianImageFilter/Documentation.html <http://itk.org/ITKExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussianImageFilter/Documentation.html>
http://itk.org/ITKExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussianImageFilterWithVectorInput/Documentation.html <http://itk.org/ITKExamples/src/Filtering/ImageGradient/ApplyGradientRecursiveGaussianImageFilterWithVectorInput/Documentation.html>

They were used on 2D images, so I guess extending to 3D should work, though I did not test it.
I used vectorIndexSelectionCastImageFilter to extract the images for each component.

A good help is to save the output of the GradientRecursiceGaussianFilter to a .mha file, and open if with Paraview.
There you will see the different components with their names.

If you want the magnitude, there is a VectorMagnitudeImageFilter (see the first example).

Hope that helps. I would be interested to know if everything is fine with 3D images using this filter; I never found the time
to test it thoroughly.

Michka


> On 17 Apr 2015, at 18:49, Pol Monsó Purtí <lluna.nova at gmail.com> wrote:
> 
> 
> Until somebody can explain why the output of the aforementioned filter has the same values on each component, here's how to get the gradient on each dimension:
> 
> //features
>   typedef itk::RecursiveGaussianImageFilter< TImageType, GradientImageType > GradientFilterType;
>   typename GradientFilterType::Pointer gradientFilter = GradientFilterType::New();
>   gradientFilter->SetInput(imageROIextractor->GetOutput());
>   float sigma = 3.5;
>   gradientFilter->SetSigma( sigma );
>   gradientFilter->SetFirstOrder();
>   std::vector< typename GradientImageType::Pointer > gradients(TImageType::ImageDimension);
> 
>   try {
>     for(unsigned int dim = 0; dim < TImageType::ImageDimension; dim++) {
>       gradientFilter->SetDirection(dim);
>       gradientFilter->Update();
>       gradients[dim] = gradientFilter->GetOutput();
>       gradients[dim]->DisconnectPipeline();
>     }
>   } catch( itk::ExceptionObject & error ) {
>     std::cerr << __FILE__ << ":" << __LINE__ << " Error: " << error << std::endl;
>     return FUCKEDUP;
>   }
> 
> 
> 2015-04-17 16:01 GMT+02:00 Pol Monsó Purtí <lluna.nova at gmail.com <mailto:lluna.nova at gmail.com>>:
> Apparently, even if the default is a covariantVector of dimension ImageDimension (3), the three components of each "pixel" have the same value. So the question is still there, how do I retrieve the gradient on each dimension of an image?
> 
> 2015-04-16 15:30 GMT+02:00 Pol Monsó Purtí <lluna.nova at gmail.com <mailto:lluna.nova at gmail.com>>:
> Hello all,
> 
> The declaration of thefilter is
> 
> template<typename TInputImage, typename TOutputImage = Image< CovariantVector< typename NumericTraits< typename TInputImage::PixelType >::RealType, TInputImage::ImageDimension >, TInputImage::ImageDimension >>
> 
> In my case, ImageDimension = 3
> 
> So I have two questions.
> 
> Question number 1: 
> Does the output image hold, for each pixel, the three derivatives? Can they be accessed by
> 
> it.Get()[0] it.Get()[1] it.Get()[2]
> 
> where it is itk::ImageRegionIterator< GradientImageType > it( gradientImage, 
> gradientImage->GetRequestedRegion() );
> 
> ?
> 
> Question number 2: (just for curiosity)
> what happens when TOutputImage = Image< PixelType, Dimension> ?
> and what happens when you create a writer with the default TOutputImage and write to disk? Do the derivatives end in different channels or a magnitude is computed?
> 
> 
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