📄 itkgradientvectorflowimagefiltertest.cxx
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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkGradientVectorFlowImageFilterTest.cxx,v $
Language: C++
Date: $Date: 2007-08-20 12:47:12 $
Version: $Revision: 1.13 $
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.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include <itkImage.h>
#include <itkGradientRecursiveGaussianImageFilter.h>
#include <itkImageRegionIteratorWithIndex.h>
#include <itkCovariantVector.h>
#include <itkGradientImageFilter.h>
#include <itkGradientToMagnitudeImageFilter.h>
#include <itkDerivativeImageFilter.h>
#include <itkGradientVectorFlowImageFilter.h>
#include <itkLaplacianImageFilter.h>
int itkGradientVectorFlowImageFilterTest(int , char *[])
{
// Define the dimension of the images
const unsigned int myDimension = 2;
// Declare gradient type
typedef itk::CovariantVector<double, myDimension> myGradientType;
// Declare the types of the images
typedef itk::Image<double, myDimension> myImageType;
typedef itk::Image<myGradientType, myDimension> myGradientImageType;
// Declare the type of the index to access images
typedef itk::Index<myDimension> myIndexType;
// Declare the type of the size
typedef itk::Size<myDimension> mySizeType;
// Declare the type of the Region
typedef itk::ImageRegion<myDimension> myRegionType;
typedef itk::LaplacianImageFilter<myImageType, myImageType> myLaplacianFilterType;
typedef itk::GradientVectorFlowImageFilter<myGradientImageType, myGradientImageType>
myGVFFilterType;
typedef itk::GradientImageFilter<myImageType, double, double>
myGFilterType;
typedef itk::GradientToMagnitudeImageFilter<myGradientImageType, myImageType>
myGToMFilterType;
// Create the image
myImageType::Pointer inputImage = myImageType::New();
myImageType::Pointer interImage = myImageType::New();
myImageType::Pointer inter1Image = myImageType::New();
// Define their size, and start index
mySizeType size;
size[0] = 128;
size[1] = 128;
myIndexType start;
start.Fill(0);
myRegionType region;
region.SetIndex( start );
region.SetSize( size );
// Initialize Image A
inputImage->SetLargestPossibleRegion( region );
inputImage->SetBufferedRegion( region );
inputImage->SetRequestedRegion( region );
inputImage->Allocate();
interImage->SetLargestPossibleRegion( region );
interImage->SetBufferedRegion( region );
interImage->SetRequestedRegion( region );
interImage->Allocate();
inter1Image->SetLargestPossibleRegion( region );
inter1Image->SetBufferedRegion( region );
inter1Image->SetRequestedRegion( region );
inter1Image->Allocate();
// Declare Iterator types apropriated for each image
typedef itk::ImageRegionIteratorWithIndex<myImageType> myIteratorType;
typedef itk::ImageRegionIteratorWithIndex<
myGradientImageType> myOutputIteratorType;
// Create one iterator for the Input Image A (this is a light object)
myIteratorType it( inputImage, inputImage->GetRequestedRegion() );
// Initialize the content of Image A
std::cout << "Input Image initialization " << std::endl;
while( !it.IsAtEnd() )
{
it.Set( 0.0 );
++it;
}
size[0] = 100;
size[1] = 100;
start[0] = 14;
start[1] = 14;
// Create one iterator for an internal region
region.SetSize( size );
region.SetIndex( start );
myIteratorType itb( inputImage, region );
// Initialize the content the internal region
while( !itb.IsAtEnd() )
{
itb.Set( 100.0 );
++itb;
}
// Declare the type for the
typedef itk::GradientRecursiveGaussianImageFilter<
myImageType,
myGradientImageType
> myFilterType;
// Create a Filter
myFilterType::Pointer filter = myFilterType::New();
myGFilterType::Pointer gfilter = myGFilterType::New();
myGToMFilterType::Pointer gtomfilter = myGToMFilterType::New();
// Connect the input images
filter->SetInput( inputImage );
// Set sigma
filter->SetSigma( 2.0 );
// Execute the filter
filter->Update();
std::cout << "Filter: " << filter;
myLaplacianFilterType::Pointer m_LFilter = myLaplacianFilterType::New();
myGVFFilterType::Pointer m_GVFFilter = myGVFFilterType::New();
m_GVFFilter->SetInput(gfilter->GetOutput());
m_GVFFilter->SetLaplacianFilter(m_LFilter);
m_GVFFilter->SetNoiseLevel(500);
m_GVFFilter->SetTimeStep(0.001);
m_GVFFilter->SetIterationNum(2);
// Get the Smart Pointer to the Filter Output
// It is important to do it AFTER the filter is Updated
// Because the object connected to the output may be changed
// by another during GenerateData() call
myGradientImageType::Pointer outputImage = filter->GetOutput();
// Create an iterator for going through the output image
myOutputIteratorType itg( outputImage,
outputImage->GetRequestedRegion() );
// Print the content of the result image
std::cout << " Result " << std::endl;
gtomfilter->SetInput(filter->GetOutput());
gtomfilter->Update();
gfilter->SetInput(gtomfilter->GetOutput());
gfilter->Update();
m_GVFFilter->Update();
std::cout << m_GVFFilter->GetTimeStep() << std::endl;
std::cout << m_GVFFilter->GetNoiseLevel() << std::endl;
std::cout << m_GVFFilter->GetIterationNum() << std::endl;
myOutputIteratorType itgvf( m_GVFFilter->GetOutput(),
m_GVFFilter->GetOutput()->GetRequestedRegion() );
std::cout << "Completed" << std::endl;
// All objects should be automatically destroyed at this point
return EXIT_SUCCESS;
}
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