Compute Mean Squares Metric Between Two Images

Synopsis

Compute the mean squares metric between two images.

Results

input image

Input image 1.

input image

Input image 2.

Data from 2 images passed through Output:

[-10, -10]: 23101.7
[-10, -5]: 23205.7
[-10, 0]: 23260.4
[-10, 5]: 23064.5
[-10, 10]: 22914.5
[-5, -10]: 23271.1
[-5, -5]: 23351.3
[-5, 0]: 23401
[-5, 5]: 23185.1
[-5, 10]: 23026.5
[0, -10]: 23486.5
[0, -5]: 23538.2
[0, 0]: 23566.2
[0, 5]: 23352.1
[0, 10]: 23175.2
[5, -10]: 23590.7
[5, -5]: 23625.7
[5, 0]: 23633.4
[5, 5]: 23401.1
[5, 10]: 23196.7
[10, -10]: 23723.5
[10, -5]: 23762.9
[10, 0]: 23767.1
[10, 5]: 23504.9
[10, 10]: 23298.3

Code

C++

#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkMeanSquaresImageToImageMetric.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkTranslationTransform.h"

int
main(int argc, char * argv[])
{
  using ImageType = itk::Image<double, 2>;
  using ReaderType = itk::ImageFileReader<ImageType>;

  if (argc < 3)
  {
    std::cout << "Usage: " << argv[0] << " imageFile1 imageFile2" << std::endl;
    return EXIT_FAILURE;
  }
  ReaderType::Pointer fixedReader = ReaderType::New();
  fixedReader->SetFileName(argv[1]);
  fixedReader->Update();

  ReaderType::Pointer movingReader = ReaderType::New();
  movingReader->SetFileName(argv[2]);
  movingReader->Update();

  ImageType::Pointer fixedImage = fixedReader->GetOutput();
  ImageType::Pointer movingImage = movingReader->GetOutput();

  using MetricType = itk::MeanSquaresImageToImageMetric<ImageType, ImageType>;
  using InterpolatorType = itk::LinearInterpolateImageFunction<ImageType, double>;
  using TransformType = itk::TranslationTransform<double, 2>;

  MetricType::Pointer    metric = MetricType::New();
  TransformType::Pointer transform = TransformType::New();

  InterpolatorType::Pointer interpolator = InterpolatorType::New();
  interpolator->SetInputImage(fixedImage);

  metric->SetFixedImage(fixedImage);
  metric->SetMovingImage(movingImage);
  metric->SetFixedImageRegion(fixedImage->GetLargestPossibleRegion());
  metric->SetTransform(transform);
  metric->SetInterpolator(interpolator);

  TransformType::ParametersType params(transform->GetNumberOfParameters());
  params.Fill(0.0);

  metric->Initialize();
  for (double x = -10.0; x <= 10.0; x += 5.0)
  {
    params(0) = x;
    for (double y = -10.0; y <= 10.0; y += 5.0)
    {
      params(1) = y;
      std::cout << params << ": " << metric->GetValue(params) << std::endl;
    }
  }

  return EXIT_SUCCESS;
}

Classes demonstrated