CLUtilities/test/mitkGlobalFeaturesTest.cpp

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/*============================================================================

The Medical Imaging Interaction Toolkit (MITK)

Copyright (c) German Cancer Research Center (DKFZ)
All rights reserved.

Use of this source code is governed by a 3-clause BSD license that can be
found in the LICENSE file.

============================================================================*/

#include <mitkTestingMacros.h>
#include <mitkTestFixture.h>
#include "mitkIOUtil.h"

#include <mitkImageCast.h>
#include <mitkGIFFirstOrderStatistics.h>
#include <mitkGIFCooccurenceMatrix.h>
#include <mitkGIFGreyLevelRunLength.h>
#include <cmath>

#include <mitkImageGenerator.h>

template <typename TPixelType>
static mitk::Image::Pointer GenerateMaskImage(unsigned int dimX,
                                              unsigned int dimY,
                                              unsigned int dimZ,
                                              float spacingX = 1,
                                              float spacingY = 1,
                                              float spacingZ = 1)
{
  typedef itk::Image< TPixelType, 3 > ImageType;
  typename ImageType::RegionType imageRegion;
  imageRegion.SetSize(0, dimX);
  imageRegion.SetSize(1, dimY);
  imageRegion.SetSize(2, dimZ);
  typename ImageType::SpacingType spacing;
  spacing[0] = spacingX;
  spacing[1] = spacingY;
  spacing[2] = spacingZ;

  mitk::Point3D                       origin; origin.Fill(0.0);
  itk::Matrix<double, 3, 3>           directionMatrix; directionMatrix.SetIdentity();

  typename ImageType::Pointer image = ImageType::New();
  image->SetSpacing( spacing );
  image->SetOrigin( origin );
  image->SetDirection( directionMatrix );
  image->SetLargestPossibleRegion( imageRegion );
  image->SetBufferedRegion( imageRegion );
  image->SetRequestedRegion( imageRegion );
  image->Allocate();
  image->FillBuffer(1);

  mitk::Image::Pointer mitkImage = mitk::Image::New();
  mitkImage->InitializeByItk( image.GetPointer() );
  mitkImage->SetVolume( image->GetBufferPointer() );
  return mitkImage;
}

template <typename TPixelType>
static mitk::Image::Pointer GenerateGradientWithDimXImage(unsigned int dimX,
                                                          unsigned int dimY,
                                                          unsigned int dimZ,
                                                          float spacingX = 1,
                                                          float spacingY = 1,
                                                          float spacingZ = 1)
{
  typedef itk::Image< TPixelType, 3 > ImageType;
  typename ImageType::RegionType imageRegion;
  imageRegion.SetSize(0, dimX);
  imageRegion.SetSize(1, dimY);
  imageRegion.SetSize(2, dimZ);
  typename ImageType::SpacingType spacing;
  spacing[0] = spacingX;
  spacing[1] = spacingY;
  spacing[2] = spacingZ;

  mitk::Point3D                       origin; origin.Fill(0.0);
  itk::Matrix<double, 3, 3>           directionMatrix; directionMatrix.SetIdentity();

  typename ImageType::Pointer image = ImageType::New();
  image->SetSpacing( spacing );
  image->SetOrigin( origin );
  image->SetDirection( directionMatrix );
  image->SetLargestPossibleRegion( imageRegion );
  image->SetBufferedRegion( imageRegion );
  image->SetRequestedRegion( imageRegion );
  image->Allocate();
  image->FillBuffer(0.0);

  typedef itk::ImageRegionIterator<ImageType>      IteratorOutputType;
  IteratorOutputType it(image, imageRegion);
  it.GoToBegin();

  TPixelType val = 0;
  while(!it.IsAtEnd())
  {
    it.Set(val % dimX);
    val++;
    ++it;
  }

  mitk::Image::Pointer mitkImage = mitk::Image::New();
  mitkImage->InitializeByItk( image.GetPointer() );
  mitkImage->SetVolume( image->GetBufferPointer() );
  return mitkImage;
}


class mitkGlobalFeaturesTestSuite : public mitk::TestFixture
{
  CPPUNIT_TEST_SUITE(mitkGlobalFeaturesTestSuite  );

  MITK_TEST(FirstOrder_SinglePoint);
  MITK_TEST(FirstOrder_QubicArea);
  //MITK_TEST(RunLenght_QubicArea);
  MITK_TEST(Coocurrence_QubicArea);
  //MITK_TEST(TestFirstOrderStatistic);
  //  MITK_TEST(TestThreadedDecisionForest);

  CPPUNIT_TEST_SUITE_END();

private:

  typedef itk::Image<double,3> ImageType;
  typedef itk::Image<unsigned char,3> MaskType;

  mitk::Image::Pointer m_Image,m_Mask,m_Mask1;
  ImageType::Pointer m_ItkImage;
  MaskType::Pointer m_ItkMask,m_ItkMask1;

  mitk::Image::Pointer m_GradientImage, m_GradientMask;

public:

  void setUp(void) override
  {
    // Load Image Data
    m_Image = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Pic3D.nrrd"));
    mitk::CastToItkImage(m_Image,m_ItkImage);

    // Create a single mask with only one pixel within the regions
    mitk::Image::Pointer mask1 = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Pic3D.nrrd"));
    mitk::CastToItkImage(mask1,m_ItkMask);
    m_ItkMask->FillBuffer(0);
    MaskType::IndexType index;
    index[0]=88;index[1]=81;index[2]=13;
    m_ItkMask->SetPixel(index, 1);
    MITK_INFO << "Pixel Value: "<<m_ItkImage->GetPixel(index);
    mitk::CastToMitkImage(m_ItkMask, m_Mask);

    // Create a mask with a covered region
    mitk::Image::Pointer lmask1 = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Pic3D.nrrd"));
    mitk::CastToItkImage(lmask1,m_ItkMask1);
    m_ItkMask1->FillBuffer(0);
    int range=2;
    for (int x = 88-range;x < 88+range+1;++x)
    {
      for (int y=81-range;y<81+range+1;++y)
      {
        for (int z=13-range;z<13+range+1;++z)
        {
          index[0] = x;
          index[1] = y;
          index[2] = z;
          //MITK_INFO << "Pixel: " <<m_ItkImage->GetPixel(index);
          m_ItkMask1->SetPixel(index, 1);
        }
      }
    }
    mitk::CastToMitkImage(m_ItkMask1, m_Mask1);

    m_GradientImage=GenerateGradientWithDimXImage<unsigned char>(5,5,5);
    m_GradientMask = GenerateMaskImage<unsigned char>(5,5,5);
  }

  void FirstOrder_SinglePoint()
  {
    mitk::GIFFirstOrderStatistics::Pointer calculator = mitk::GIFFirstOrderStatistics::New();
    //calculator->SetHistogramSize(4096);
    //calculator->SetUseCtRange(true);
    auto features = calculator->CalculateFeatures(m_Image, m_Mask);

    std::map<std::string, double> results;
    for (auto iter=features.begin(); iter!=features.end();++iter)
    {
      results[(*iter).first]=(*iter).second;
      MITK_INFO << (*iter).first << " : " << (*iter).second;
    }

    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The range of a single pixel should  be 0",0.0, results["FirstOrder Range"], 0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The uniformity of a single pixel should  be 1",1.0, results["FirstOrder Uniformity"], 0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The entropy of a single pixel should  be 0",0.0, results["FirstOrder Entropy"], 0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Root-Means-Square of a single pixel with (-352) should  be 352",352.0, results["FirstOrder RMS"], 0.01);
    CPPUNIT_ASSERT_EQUAL_MESSAGE("The Kurtosis of a single pixel should be undefined",results["FirstOrder Kurtosis"]==results["FirstOrder Kurtosis"], false);
    CPPUNIT_ASSERT_EQUAL_MESSAGE("The Skewness of a single pixel should be undefined",results["FirstOrder Skewness"]==results["FirstOrder Skewness"], false);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Mean absolute deviation of a single pixel with (-352) should  be 0",0, results["FirstOrder Mean absolute deviation"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Covered image intensity range of a single pixel with (-352) should be 0",0, results["FirstOrder Covered Image Intensity Range"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Minimum of a single pixel with (-352) should be -352",-352, results["FirstOrder Minimum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Maximum of a single pixel with (-352) should be -352",-352, results["FirstOrder Maximum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Mean of a single pixel with (-352) should be -352",-352, results["FirstOrder Mean"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Variance (corrected) of a single pixel with (-352) should be 0",0, results["FirstOrder Variance"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Sum of a single pixel with (-352) should be -352",-352, results["FirstOrder Sum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Median of a single pixel with (-352) should be -352",-352, results["FirstOrder Median"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Standard deviation (corrected) of a single pixel with (-352) should be -352",0, results["FirstOrder Standard deviation"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The number of voxels of a single pixel should be 1",1, results["FirstOrder No. of Voxel"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Energy of a single pixel should be 352*352",352*352, results["FirstOrder Energy"], 0.0);
    //  MITK_ASSERT_EQUAL(results["FirstOrder Range"]==0.0,true,"The range of a single pixel should  be 0");
  }

  void FirstOrder_QubicArea()
  {
    mitk::GIFFirstOrderStatistics::Pointer calculator = mitk::GIFFirstOrderStatistics::New();
    //calculator->SetHistogramSize(4096);
    //calculator->SetUseCtRange(true);
    auto features = calculator->CalculateFeatures(m_Image, m_Mask1);

    std::map<std::string, double> results;
    for (auto iter=features.begin(); iter!=features.end();++iter)
    {
      results[(*iter).first]=(*iter).second;
      MITK_INFO << (*iter).first << " : " << (*iter).second;
    }

    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The range should be 981",981, results["FirstOrder Range"], 0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Root-Means-Square of a single pixel with (-352) should  be 352",402.895778, results["FirstOrder RMS"], 0.01);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Minimum of a single pixel with (-352) should be -352",-937, results["FirstOrder Minimum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Maximum of a single pixel with (-352) should be -352",44, results["FirstOrder Maximum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Mean of a single pixel with (-352) should be -352",-304.448, results["FirstOrder Mean"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Sum of a single pixel with (-352) should be -352",-38056, results["FirstOrder Sum"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Median of a single pixel with (-352) should be -352",-202, results["FirstOrder Median"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The number of voxels of a single pixel should be 1",125, results["FirstOrder No. of Voxel"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Standard deviation (corrected) of a single pixel with (-352) should be -352",264.949066, results["FirstOrder Standard deviation"], 0.000001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Energy of a single pixel should be 352*352",20290626, results["FirstOrder Energy"], 0.0);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The uniformity of a single pixel should  be 1",0.0088960, results["FirstOrder Uniformity"], 0.0000001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The entropy of a single pixel should  be 0",-6.853784285, results["FirstOrder Entropy"], 0.000000005);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Variance (corrected) of a single pixel with (-352) should be 0",70198.0074, results["FirstOrder Variance"], 0.0001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Kurtosis of a single pixel should  be 0",2.63480121, results["FirstOrder Kurtosis"], 0.0001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Skewness of a single pixel should  be 0",-0.91817318, results["FirstOrder Skewness"], 0.00001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Mean absolute deviation of a single pixel with (-352) should  be 0",219.348608, results["FirstOrder Mean absolute deviation"], 0.000001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The Covered image intensity range of a single pixel with (-352) should be 0",0.41149329, results["FirstOrder Covered Image Intensity Range"], 0.000001);
  }

  void RunLenght_QubicArea()
  {
    mitk::GIFGreyLevelRunLength::Pointer calculator = mitk::GIFGreyLevelRunLength::New();
    //calculator->SetHistogramSize(4096);
    auto features = calculator->CalculateFeatures(m_Image, m_Mask1);

    std::map<std::string, double> results;
    for (auto iter=features.begin(); iter!=features.end();++iter)
    {
      results[(*iter).first]=(*iter).second;
      MITK_INFO << (*iter).first << " : " << (*iter).second;
    }
  }

  void Coocurrence_QubicArea()
  {
    /*
    * Expected Matrix: (Direction 0,0,1)
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    * | 0  | 20 | 0  | 0  | 0  |
    * |------------------------|
    * | 0  | 0  | 20 | 0  | 0  |
    * |------------------------|
    * | 0  | 0  | 0  | 20 | 0  |
    * |------------------------|
    * | 0  | 0  | 0  | 0  | 20 |
    * |------------------------|

    * Expected Matrix: (Direction (1,0,0),(0,1,0))
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    * | 20 | 0  | 0  | 0  | 0  |
    * |------------------------|
    */

    mitk::GIFCooccurenceMatrix::Pointer calculator = mitk::GIFCooccurenceMatrix::New();
    //calculator->SetHistogramSize(4096);
    //calculator->SetUseCtRange(true);
    //calculator->SetRange(981);
  calculator->SetDirection(1);
    auto features = calculator->CalculateFeatures(m_GradientImage, m_GradientMask);

    std::map<std::string, double> results;
    for (auto iter=features.begin(); iter!=features.end();++iter)
    {
      results[(*iter).first]=(*iter).second;
      MITK_INFO << (*iter).first << " : " << (*iter).second;
    }
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean energy value should be 0.2",0.2, results["co-occ. (1) Energy Means"], mitk::eps);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean entropy value should be 0.2",2.321928, results["co-occ. (1) Entropy Means"], 0.000001);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean contrast value should be 0.0",0, results["co-occ. (1) Contrast Means"], mitk::eps);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean dissimilarity value should be 0.0",0, results["co-occ. (1) Dissimilarity Means"], mitk::eps);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean homogenity1 value should be 1.0",1, results["co-occ. (1) Homogeneity1 Means"], mitk::eps);
    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("The mean InverseDifferenceMoment value should be 1.0",1, results["co-occ. (1) InverseDifferenceMoment Means"], mitk::eps);
  }
};

MITK_TEST_SUITE_REGISTRATION(mitkGlobalFeatures)