/*========================================================================= * * 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 "itkKullbackLeiblerCompareHistogramImageToImageMetric.h" #include "itkTranslationTransform.h" #include "itkTestingMacros.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 *[]) { // Create two simple images. constexpr unsigned int ImageDimension = 2; using PixelType = double; using CoordinateRepresentationType = double; // Allocate Images using MovingImageType = itk::Image; using FixedImageType = itk::Image; // Declare Gaussian Sources using MovingImageSourceType = itk::GaussianImageSource; using FixedImageSourceType = itk::GaussianImageSource; // 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); ITK_TRY_EXPECT_NO_EXCEPTION(movingImageSource->Update()); // Force the filter to run ITK_TRY_EXPECT_NO_EXCEPTION(fixedImageSource->Update()); // Force the filter to run MovingImageType::Pointer movingImage = movingImageSource->GetOutput(); FixedImageType::Pointer fixedImage = fixedImageSource->GetOutput(); // Set up the metric. using MetricType = itk::KullbackLeiblerCompareHistogramImageToImageMetric; using TransformBaseType = MetricType::TransformType; using ScalesType = MetricType::ScalesType; using ParametersType = TransformBaseType::ParametersType; auto metric = MetricType::New(); ITK_EXERCISE_BASIC_OBJECT_METHODS( metric, KullbackLeiblerCompareHistogramImageToImageMetric, CompareHistogramImageToImageMetric); auto epsilon = 1e-12; metric->SetEpsilon(epsilon); ITK_TEST_SET_GET_VALUE(epsilon, metric->GetEpsilon()); 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; auto transform = TransformType::New(); metric->SetTransform(transform); // Set up an interpolator. using InterpolatorType = itk::LinearInterpolateImageFunction; 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 < transform->GetNumberOfParameters(); ++k) { scales[k] = 1; } metric->SetDerivativeStepLengthScales(scales); // Now set up the Training Stuff metric->SetTrainingTransform(transform); ITK_TEST_SET_GET_VALUE(transform, metric->GetTrainingTransform()); metric->SetTrainingFixedImage(fixedImage); ITK_TEST_SET_GET_VALUE(fixedImage, metric->GetTrainingFixedImage()); metric->SetTrainingFixedImageRegion(fixedImage->GetBufferedRegion()); ITK_TEST_SET_GET_VALUE(fixedImage->GetBufferedRegion(), metric->GetTrainingFixedImageRegion()); metric->SetTrainingMovingImage(movingImage); ITK_TEST_SET_GET_VALUE(movingImage, metric->GetTrainingMovingImage()); metric->SetTrainingInterpolator(interpolator); ITK_TEST_SET_GET_VALUE(interpolator, metric->GetTrainingInterpolator()); ITK_TEST_EXPECT_EQUAL(transform->GetNumberOfParameters(), metric->GetNumberOfParameters()); // 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; std::cout << "Test finished." << std::endl; return EXIT_SUCCESS; }