[Insight-users] itkDemonsRegistrationFilter
Lydia Ng
lng at insightful.com
Wed Jun 2 20:17:23 EDT 2004
Ping,
>From your attached code - it looks like you haven't changed all your code
from 2 to 3.
> typedef itk::Image< float, 2 > InternalImageType;
> typedef itk::Vector< float, 2 >
> VectorPixelType;
> typedef itk::Image< VectorPixelType, 2 >
> DeformationFieldType;
and
> const unsigned int Dimension = 2;
> typedef unsigned short PixelType;
- Lydia
> -----Original Message-----
> From: ping chen [mailto:miw2k at yahoo.com]
> Sent: Wednesday, June 02, 2004 12:07 PM
> To: Luis Ibanez
> Cc: insight-users at itk.org; Miller, James V (Research)
> Subject: [Insight-users] itkDemonsRegistrationFilter
>
> Hi Luis,
>
> I am trying to use Demons registration example
> DeformableRegistration2.cxx on 3d brain images. i have
> changed the demensions from 2 to 3. but the output
> warped image is still only one 2d slice. can you tell
> me why? Thanks for your help.
>
> -Ping
>
> below is the code DeformableRegistration2.cxx code i
> am using:
>
> /*========================================================================
> =
>
> Program: Insight Segmentation & Registration
> Toolkit
> Module: $RCSfile: DeformableRegistration2.cxx,v $
> Language: C++
> Date: $Date: 2004/04/20 20:19:47 $
> Version: $Revision: 1.24 $
>
> Copyright (c) Insight Software Consortium. All
> rights reserved.
> See ITKCopyright.txt or
> http://www.itk.org/HTML/Copyright.htm for details.
>
> This software is distributed WITHOUT ANY
> WARRANTY; without even
> the implied warranty of MERCHANTABILITY or
> FITNESS FOR A PARTICULAR
> PURPOSE. See the above copyright notices for
> more information.
>
> =========================================================================*
> /
>
> #include "itkImageFileReader.h"
> #include "itkImageFileWriter.h"
>
> #include "itkImageRegionIterator.h"
>
> // Software Guide : BeginLatex
> //
> // This example demostrates how to use the ``demons''
> algorithm to deformably
> // register two images. The first step is to include
> the header files.
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> #include "itkDemonsRegistrationFilter.h"
> #include "itkHistogramMatchingImageFilter.h"
> #include "itkCastImageFilter.h"
> #include "itkWarpImageFilter.h"
> #include "itkLinearInterpolateImageFunction.h"
> // Software Guide : EndCodeSnippet
>
>
>
>
>
> // The following section of code implements a Command
> observer
> // that will monitor the evolution of the
> registration process.
> //
> class CommandIterationUpdate : public itk::Command
> {
> public:
> typedef CommandIterationUpdate Self;
> typedef itk::Command Superclass;
> typedef itk::SmartPointer<CommandIterationUpdate>
> Pointer;
> itkNewMacro( CommandIterationUpdate );
> protected:
> CommandIterationUpdate() {};
>
> typedef itk::Image< float, 2 > InternalImageType;
> typedef itk::Vector< float, 2 >
> VectorPixelType;
> typedef itk::Image< VectorPixelType, 2 >
> DeformationFieldType;
>
> typedef itk::DemonsRegistrationFilter<
> InternalImageType,
> InternalImageType,
> DeformationFieldType>
> RegistrationFilterType;
>
> public:
>
> void Execute(itk::Object *caller, const
> itk::EventObject & event)
> {
> Execute( (const itk::Object *)caller, event);
> }
>
> void Execute(const itk::Object * object, const
> itk::EventObject & event)
> {
> const RegistrationFilterType * filter =
> dynamic_cast< const RegistrationFilterType *
> >( object );
> if( typeid( event ) != typeid(
> itk::IterationEvent ) )
> {
> return;
> }
> std::cout << filter->GetMetric() << std::endl;
> }
> };
>
>
>
>
>
>
> int main( int argc, char *argv[] )
> {
> if( argc < 4 )
> {
> std::cerr << "Missing Parameters " << std::endl;
> std::cerr << "Usage: " << argv[0];
> std::cerr << " fixedImageFile movingImageFile ";
> std::cerr << " outputImageFile " << std::endl;
> std::cerr << " [outputDeformationFieldFile] " <<
> std::endl;
> return 1;
> }
>
> // Software Guide : BeginLatex
> //
> // Second, we declare the types of the images.
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> const unsigned int Dimension = 2;
> typedef unsigned short PixelType;
>
> typedef itk::Image< PixelType, Dimension >
> FixedImageType;
> typedef itk::Image< PixelType, Dimension >
> MovingImageType;
> // Software Guide : EndCodeSnippet
>
> // Set up the file readers
> typedef itk::ImageFileReader< FixedImageType >
> FixedImageReaderType;
> typedef itk::ImageFileReader< MovingImageType >
> MovingImageReaderType;
>
> FixedImageReaderType::Pointer fixedImageReader =
> FixedImageReaderType::New();
> MovingImageReaderType::Pointer movingImageReader =
> MovingImageReaderType::New();
>
> fixedImageReader->SetFileName( argv[1] );
> movingImageReader->SetFileName( argv[2] );
>
>
> // Software Guide : BeginLatex
> //
> // Image file readers are set up in a similar
> fashion to previous examples.
> // To support the re-mapping of the moving image
> intensity, we declare an
> // internal image type with a floating point pixel
> type and cast the input
> // images to the internal image type.
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> typedef float InternalPixelType;
> typedef itk::Image< InternalPixelType, Dimension >
> InternalImageType;
> typedef itk::CastImageFilter< FixedImageType,
> InternalImageType >
> FixedImageCasterType;
> typedef itk::CastImageFilter< MovingImageType,
> InternalImageType >
> MovingImageCasterType;
>
> FixedImageCasterType::Pointer fixedImageCaster =
> FixedImageCasterType::New();
> MovingImageCasterType::Pointer movingImageCaster =
> MovingImageCasterType::New();
>
> fixedImageCaster->SetInput(
> fixedImageReader->GetOutput() );
> movingImageCaster->SetInput(
> movingImageReader->GetOutput() );
> // Software Guide : EndCodeSnippet
>
> // Software Guide : BeginLatex
> //
> // The demons algorithm relies on the assumption
> that pixels representing the
> // same homologous point on an object have the same
> intensity on both the
> // fixed and moving images to be registered. In this
> example, we will
> // preprocess the moving image to match the
> intensity between the images
> // using the \doxygen{HistogramMatchingImageFilter}.
>
> //
> // \index{itk::HistogramMatchingImageFilter}
> //
> // The basic idea is to match the histograms of the
> two images at a user-specified number of quantile
> values. For robustness, the histograms are
> // matched so that the background pixels are
> excluded from both histograms.
> // For MR images, a simple procedure is to exclude
> all gray values that are
> // smaller than the mean gray value of the image.
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> typedef itk::HistogramMatchingImageFilter<
> InternalImageType,
> InternalImageType
> > MatchingFilterType;
> MatchingFilterType::Pointer matcher =
> MatchingFilterType::New();
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // For this example, we set the moving image as the
> source or input image and
> // the fixed image as the reference image.
> //
> //
> \index{itk::HistogramMatchingImageFilter!SetInput()}
> //
> \index{itk::HistogramMatchingImageFilter!SetSourceImage()}
> //
> \index{itk::HistogramMatchingImageFilter!SetReferenceImage()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> matcher->SetInput( movingImageCaster->GetOutput() );
> matcher->SetReferenceImage(
> fixedImageCaster->GetOutput() );
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // We then select the number of bins to represent
> the histograms and the
> // number of points or quantile values where the
> histogram is to be
> // matched.
> //
> //
> \index{itk::HistogramMatchingImageFilter!SetNumberOfHistogramLevels()}
> //
> \index{itk::HistogramMatchingImageFilter!SetNumberOfMatchPoints()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> matcher->SetNumberOfHistogramLevels( 1024 );
> matcher->SetNumberOfMatchPoints( 7 );
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // Simple background extraction is done by
> thresholding at the mean
> // intensity.
> //
> //
> \index{itk::HistogramMatchingImageFilter!ThresholdAtMeanIntensityOn()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> matcher->ThresholdAtMeanIntensityOn();
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // In the \doxygen{DemonsRegistrationFilter}, the
> deformation field is
> // represented as an image whose pixels are floating
> point vectors.
> //
> // \index{itk::DemonsRegistrationFilter}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> typedef itk::Vector< float, Dimension >
> VectorPixelType;
> typedef itk::Image< VectorPixelType, Dimension >
> DeformationFieldType;
> typedef itk::DemonsRegistrationFilter<
> InternalImageType,
> InternalImageType,
> DeformationFieldType>
> RegistrationFilterType;
> RegistrationFilterType::Pointer filter =
> RegistrationFilterType::New();
> // Software Guide : EndCodeSnippet
>
>
>
>
>
> // Create the Command observer and register it with
> the registration filter.
> //
> CommandIterationUpdate::Pointer observer =
> CommandIterationUpdate::New();
> filter->AddObserver( itk::IterationEvent(), observer
> );
>
>
>
>
> // Software Guide : BeginLatex
> //
> // The input fixed image is simply the output of the
> fixed image casting
> // filter. The input moving image is the output of
> the histogram matching
> // filter.
> //
> //
> \index{itk::DemonsRegistrationFilter!SetFixedImage()}
> //
> \index{itk::DemonsRegistrationFilter!SetMovingImage()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> filter->SetFixedImage( fixedImageCaster->GetOutput()
> );
> filter->SetMovingImage( matcher->GetOutput() );
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // The demons registration filter has two
> parameters: the number of
> // iterations to be performed and the standard
> deviation of the Gaussian
> // smoothing kernel to be applied to the deformation
> field after each
> // iteration.
> //
> \index{itk::DemonsRegistrationFilter!SetNumberOfIterations()}
> //
> \index{itk::DemonsRegistrationFilter!SetStandardDeviations()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> filter->SetNumberOfIterations( 150 );
> filter->SetStandardDeviations( 1.0 );
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // The registration algorithm is triggered by
> updating the filter. The
> // filter output is the computed deformation field.
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> filter->Update();
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // The \doxygen{WarpImageFilter} can be used to warp
> the moving image with
> // the output deformation field. Like the
> \doxygen{ResampleImageFilter},
> // the WarpImageFilter requires the specification of
> the input image to be
> // resampled, an input image interpolator, and the
> output image spacing and
> // origin.
> //
> // \index{itk::WarpImageFilter}
> // \index{itk::WarpImageFilter!SetInput()}
> // \index{itk::WarpImageFilter!SetInterpolator()}
> // \index{itk::WarpImageFilter!SetOutputSpacing()}
> // \index{itk::WarpImageFilter!SetOutputOrigin()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> typedef itk::WarpImageFilter<
> MovingImageType,
> MovingImageType,
> DeformationFieldType >
> WarperType;
> typedef itk::LinearInterpolateImageFunction<
> MovingImageType,
> double >
> InterpolatorType;
> WarperType::Pointer warper = WarperType::New();
> InterpolatorType::Pointer interpolator =
> InterpolatorType::New();
> FixedImageType::Pointer fixedImage =
> fixedImageReader->GetOutput();
>
> warper->SetInput( movingImageReader->GetOutput() );
> warper->SetInterpolator( interpolator );
> warper->SetOutputSpacing( fixedImage->GetSpacing()
> );
> warper->SetOutputOrigin( fixedImage->GetOrigin() );
> // Software Guide : EndCodeSnippet
>
>
> // Software Guide : BeginLatex
> //
> // Unlike the ResampleImageFilter, the
> WarpImageFilter
> // warps or transform the input image with respect
> to the deformation field
> // represented by an image of vectors. The
> resulting warped or resampled
> // image is written to file as per previous
> examples.
> //
> //
> \index{itk::WarpImageFilter!SetDeformationField()}
> //
> // Software Guide : EndLatex
>
> // Software Guide : BeginCodeSnippet
> warper->SetDeformationField( filter->GetOutput() );
> // Software Guide : EndCodeSnippet
>
>
> // Write warped image out to file
> typedef unsigned char OutputPixelType;
> typedef itk::Image< OutputPixelType, Dimension >
> OutputImageType;
> typedef itk::CastImageFilter<
> MovingImageType,
> OutputImageType >
> CastFilterType;
> typedef itk::ImageFileWriter< OutputImageType >
> WriterType;
>
> WriterType::Pointer writer =
> WriterType::New();
> CastFilterType::Pointer caster =
> CastFilterType::New();
>
> writer->SetFileName( argv[3] );
>
> caster->SetInput( warper->GetOutput() );
> writer->SetInput( caster->GetOutput() );
> writer->Update();
>
>
> // Software Guide : BeginLatex
> //
> // Let's execute this example using the rat lung
> data from the previous example.
> // The associated data files can be found in
> \code{Examples/Data}:
> //
> // \begin{itemize}
> // \item \code{RatLungSlice1.mha}
> // \item \code{RatLungSlice2.mha}
> // \end{itemize}
> //
> // \begin{figure} \center
> //
> \includegraphics[width=0.44\textwidth]{DeformableRegistration2Checkerboard
> Before.eps}
> //
> \includegraphics[width=0.44\textwidth]{DeformableRegistration2Checkerboard
> After.eps}
> // \itkcaption[Demon's deformable registration
> output]{Checkerboard comparisons
> // before and after demons-based deformable
> registration.}
> // \label{fig:DeformableRegistration2Output}
> // \end{figure}
> //
> // The result of the demons-based deformable
> registration is presented in
> // Figure \ref{fig:DeformableRegistration2Output}.
> The checkerboard
> // comparision shows that the algorithm was able to
> recover the misalignment
> // due to expiration.
> //
> // Software Guide : EndLatex
>
>
>
> // Software Guide : BeginLatex
> //
> // It may be also desirable to write the deformation
> field as an image of
> // vectors. This can be done with the following
> code.
> //
> // Software Guide : EndLatex
>
> if( argc > 4 ) // if a fourth line argument has been
> provided...
> {
>
> // Software Guide : BeginCodeSnippet
> typedef itk::ImageFileWriter< DeformationFieldType >
> FieldWriterType;
> FieldWriterType::Pointer fieldWriter =
> FieldWriterType::New();
> fieldWriter->SetFileName( argv[4] );
> fieldWriter->SetInput( filter->GetOutput() );
>
> fieldWriter->Update();
> // Software Guide : EndCodeSnippet
>
> // Software Guide : BeginLatex
> //
> // Note that the file format used for writing the
> deformation field must be
> // capable of representing multiple components per
> pixel. This is the case
> // for the MetaImage and VTK fileformats for
> example.
> //
> // Software Guide : EndLatex
>
> }
>
>
> if( argc > 5 ) // if a fifth line argument has been
> provided...
> {
>
> typedef DeformationFieldType VectorImage2DType;
> typedef DeformationFieldType::PixelType
> Vector2DType;
>
> VectorImage2DType::ConstPointer vectorImage2D =
> filter->GetOutput();
>
> VectorImage2DType::RegionType region2D =
> vectorImage2D->GetBufferedRegion();
> VectorImage2DType::IndexType index2D =
> region2D.GetIndex();
> VectorImage2DType::SizeType size2D =
> region2D.GetSize();
>
>
> typedef itk::Vector< float, 3 > Vector3DType;
> typedef itk::Image< Vector3DType, 3 >
> VectorImage3DType;
>
> typedef itk::ImageFileWriter< VectorImage3DType >
> WriterType;
>
> WriterType::Pointer writer3D = WriterType::New();
>
> VectorImage3DType::Pointer vectorImage3D =
> VectorImage3DType::New();
>
> VectorImage3DType::RegionType region3D;
> VectorImage3DType::IndexType index3D;
> VectorImage3DType::SizeType size3D;
>
> index3D[0] = index2D[0];
> index3D[1] = index2D[1];
> index3D[2] = 0;
>
> size3D[0] = size2D[0];
> size3D[1] = size2D[1];
> size3D[2] = 1;
>
> region3D.SetSize( size3D );
> region3D.SetIndex( index3D );
>
> vectorImage3D->SetRegions( region3D );
> vectorImage3D->Allocate();
>
> typedef itk::ImageRegionConstIterator<
> VectorImage2DType > Iterator2DType;
>
> typedef itk::ImageRegionIterator< VectorImage3DType
> > Iterator3DType;
>
> Iterator2DType it2( vectorImage2D, region2D );
> Iterator3DType it3( vectorImage3D, region3D );
>
> it2.GoToBegin();
> it3.GoToBegin();
>
> Vector2DType vector2D;
> Vector3DType vector3D;
>
> vector3D[2] = 0; // set Z component to zero.
>
> while( !it2.IsAtEnd() )
> {
> vector2D = it2.Get();
> vector3D[0] = vector2D[0];
> vector3D[1] = vector2D[1];
> it3.Set( vector3D );
> ++it2;
> ++it3;
> }
>
>
> writer3D->SetInput( vectorImage3D );
>
> writer3D->SetFileName( argv[5] );
>
> try
> {
> writer3D->Update();
> }
> catch( itk::ExceptionObject & excp )
> {
> std::cerr << excp << std::endl;
> return -1;
> }
>
>
> }
>
>
>
> return 0;
> }
>
>
>
>
>
>
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