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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#include "itkGaussianImageSource.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkKullbackLeiblerCompareHistogramImageToImageMetric.h"
#include "itkTranslationTransform.h"
/** This test uses two 2D-Gaussians (standard deviation RegionSize/2).
This test computes the mutual information between the two images.
*/
int itkCompareHistogramImageToImageMetricTest(int , char* [])
{
try {
// Create two simple images.
const unsigned int ImageDimension = 2;
typedef double PixelType;
typedef double CoordinateRepresentationType;
//Allocate Images
typedef itk::Image<PixelType,ImageDimension> MovingImageType;
typedef itk::Image<PixelType,ImageDimension> FixedImageType;
// Declare Gaussian Sources
typedef itk::GaussianImageSource<MovingImageType> MovingImageSourceType;
typedef itk::GaussianImageSource<FixedImageType> FixedImageSourceType;
// Note: the following declarations are classical arrays
FixedImageType::SizeValueType fixedImageSize[] = {100, 100};
MovingImageType::SizeValueType movingImageSize[] = {100, 100};
FixedImageType::SpacingValueType fixedImageSpacing[] = {1.0f, 1.0f};
MovingImageType::SpacingValueType movingImageSpacing[] = {1.0f, 1.0f};
FixedImageType::PointValueType fixedImageOrigin[] = {0.0f, 0.0f};
MovingImageType::PointValueType movingImageOrigin[] = {0.0f, 0.0f};
MovingImageSourceType::Pointer movingImageSource =
MovingImageSourceType::New();
FixedImageSourceType::Pointer fixedImageSource =
FixedImageSourceType::New();
movingImageSource->SetSize(movingImageSize);
movingImageSource->SetOrigin(movingImageOrigin);
movingImageSource->SetSpacing(movingImageSpacing);
movingImageSource->SetNormalized(false);
movingImageSource->SetScale(250.0f);
fixedImageSource->SetSize(fixedImageSize);
fixedImageSource->SetOrigin(fixedImageOrigin);
fixedImageSource->SetSpacing(fixedImageSpacing);
fixedImageSource->SetNormalized(false);
fixedImageSource->SetScale(250.0f);
movingImageSource->Update(); // Force the filter to run
fixedImageSource->Update(); // Force the filter to run
MovingImageType::Pointer movingImage = movingImageSource->GetOutput();
FixedImageType::Pointer fixedImage = fixedImageSource->GetOutput();
// Set up the metric.
typedef itk::KullbackLeiblerCompareHistogramImageToImageMetric<
FixedImageType,
MovingImageType
> MetricType;
typedef MetricType::TransformType TransformBaseType;
typedef MetricType::ScalesType ScalesType;
typedef TransformBaseType::ParametersType ParametersType;
MetricType::Pointer metric = MetricType::New();
unsigned int nBins = 256;
MetricType::HistogramType::SizeType histSize;
histSize.SetSize(2);
histSize[0] = nBins;
histSize[1] = nBins;
metric->SetHistogramSize(histSize);
// Plug the images into the metric.
metric->SetFixedImage(fixedImage);
metric->SetMovingImage(movingImage);
// Set up a transform.
typedef itk::TranslationTransform<CoordinateRepresentationType,
ImageDimension> TransformType;
TransformType::Pointer transform = TransformType::New();
metric->SetTransform(transform.GetPointer());
// Set up an interpolator.
typedef itk::LinearInterpolateImageFunction<MovingImageType,
double> InterpolatorType;
InterpolatorType::Pointer interpolator = InterpolatorType::New();
interpolator->SetInputImage(movingImage.GetPointer());
metric->SetInterpolator(interpolator.GetPointer());
// Define the region over which the metric will be computed.
metric->SetFixedImageRegion(fixedImage->GetBufferedRegion());
// Set up transform parameters.
ParametersType parameters(transform->GetNumberOfParameters());
for (unsigned int k = 0; k < ImageDimension; k++)
parameters[k] = 0.0f;
// Set scales for derivative calculation.
ScalesType scales(transform->GetNumberOfParameters());
for (unsigned int k = 0; k < transform->GetNumberOfParameters(); k++)
scales[k] = 1;
metric->SetDerivativeStepLengthScales(scales);
// Now set up the Training Stuff
metric->SetTrainingTransform(transform.GetPointer());
metric->SetTrainingFixedImage(fixedImage);
metric->SetTrainingFixedImageRegion(fixedImage->GetBufferedRegion());
metric->SetTrainingMovingImage(movingImage);
metric->SetTrainingInterpolator(interpolator.GetPointer());
// Initialize the metric.
metric->Initialize();
// Print out metric value and derivative.
MetricType::MeasureType measure = metric->GetValue(parameters);
MetricType::DerivativeType derivative;
metric->GetDerivative(parameters, derivative);
std::cout << "Metric value = " << measure << std::endl
<< "Derivative = " << derivative << std::endl;
// Exercise Print() method.
metric->Print(std::cout);
std::cout << "Test passed." << std::endl;
}
catch (itk::ExceptionObject& ex)
{
std::cerr << "Exception caught!" << std::endl;
std::cerr << ex << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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