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itkCorrelationCoefficientHistogramImageToImageMetricTest.cxx
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itkCorrelationCoefficientHistogramImageToImageMetricTest.cxx
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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 "itkCorrelationCoefficientHistogramImageToImageMetric.h"
#include "itkTranslationTransform.h"
/** This test uses two 2D-Gaussians (standard deviation RegionSize/2).
This test computes the correlation coefficient between the two images.
*/
int
itkCorrelationCoefficientHistogramImageToImageMetricTest(int, char *[])
{
try
{
// Create two simple images.
constexpr unsigned int ImageDimension = 2;
using PixelType = double;
using CoordinateRepresentationType = double;
// Allocate Images
using MovingImageType = itk::Image<PixelType, ImageDimension>;
using FixedImageType = itk::Image<PixelType, ImageDimension>;
// Declare Gaussian Sources
using MovingImageSourceType = itk::GaussianImageSource<MovingImageType>;
using FixedImageSourceType = itk::GaussianImageSource<FixedImageType>;
// 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 };
auto movingImageSource = MovingImageSourceType::New();
auto 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.
using MetricType = itk::CorrelationCoefficientHistogramImageToImageMetric<FixedImageType, MovingImageType>;
using TransformBaseType = MetricType::TransformType;
using ScalesType = MetricType::ScalesType;
using ParametersType = TransformBaseType::ParametersType;
auto 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.
using TransformType = itk::TranslationTransform<CoordinateRepresentationType, ImageDimension>;
auto transform = TransformType::New();
metric->SetTransform(transform);
// Set up an interpolator.
using InterpolatorType = itk::LinearInterpolateImageFunction<MovingImageType, double>;
auto interpolator = InterpolatorType::New();
interpolator->SetInputImage(movingImage);
metric->SetInterpolator(interpolator);
// 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 < ImageDimension; ++k)
{
scales[k] = 1;
}
metric->SetDerivativeStepLengthScales(scales);
// 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 (const itk::ExceptionObject & ex)
{
std::cerr << "Exception caught!" << std::endl;
std::cerr << ex << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}