diff --git a/Modules/Classification/CLUtilities/test/mitkGIFCooc2Test.cpp b/Modules/Classification/CLUtilities/test/mitkGIFCooc2Test.cpp
index 4b2026fcc6..ba0cd50b61 100644
--- a/Modules/Classification/CLUtilities/test/mitkGIFCooc2Test.cpp
+++ b/Modules/Classification/CLUtilities/test/mitkGIFCooc2Test.cpp
@@ -1,157 +1,197 @@
 /*===================================================================
 
 The Medical Imaging Interaction Toolkit (MITK)
 
 Copyright (c) German Cancer Research Center,
 Division of Medical and Biological Informatics.
 All rights reserved.
 
 This software is distributed WITHOUT ANY WARRANTY; without
 even the implied warranty of MERCHANTABILITY or FITNESS FOR
 A PARTICULAR PURPOSE.
 
 See LICENSE.txt or http://www.mitk.org for details.
 
 ===================================================================*/
 
 #include <mitkTestingMacros.h>
 #include <mitkTestFixture.h>
 #include "mitkIOUtil.h"
 #include <cmath>
 
 #include <mitkGIFCooccurenceMatrix2.h>
 
 class mitkGIFCooc2TestSuite : public mitk::TestFixture
 {
   CPPUNIT_TEST_SUITE(mitkGIFCooc2TestSuite);
 
   MITK_TEST(ImageDescription_PhantomTest_3D);
   //MITK_TEST(ImageDescription_PhantomTest_2D);
 
   CPPUNIT_TEST_SUITE_END();
 
 private:
   mitk::Image::Pointer m_IBSI_Phantom_Image_Small;
   mitk::Image::Pointer m_IBSI_Phantom_Image_Large;
   mitk::Image::Pointer m_IBSI_Phantom_Mask_Small;
   mitk::Image::Pointer m_IBSI_Phantom_Mask_Large;
 
 public:
 
   void setUp(void) override
   {
     m_IBSI_Phantom_Image_Small = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Radiomics/IBSI_Phantom_Image_Small.nrrd"));
     m_IBSI_Phantom_Image_Large = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Radiomics/IBSI_Phantom_Image_Large.nrrd"));
     m_IBSI_Phantom_Mask_Small = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Radiomics/IBSI_Phantom_Mask_Small.nrrd"));
     m_IBSI_Phantom_Mask_Large = mitk::IOUtil::Load<mitk::Image>(GetTestDataFilePath("Radiomics/IBSI_Phantom_Mask_Large.nrrd"));
   }
 
   void ImageDescription_PhantomTest_3D()
   {
     mitk::GIFCooccurenceMatrix2::Pointer featureCalculator = mitk::GIFCooccurenceMatrix2::New();
 
     featureCalculator->SetUseBinsize(true);
     featureCalculator->SetBinsize(1.0);
     featureCalculator->SetUseMinimumIntensity(true);
     featureCalculator->SetUseMaximumIntensity(true);
     featureCalculator->SetMinimumIntensity(0.5);
     featureCalculator->SetMaximumIntensity(6.5);
 
     auto featureList = featureCalculator->CalculateFeatures(m_IBSI_Phantom_Image_Large, m_IBSI_Phantom_Mask_Large);
 
     std::map<std::string, double> results;
     for (auto valuePair : featureList)
     {
       MITK_INFO << valuePair.first << " : " << valuePair.second;
       results[valuePair.first] = valuePair.second;
     }
     CPPUNIT_ASSERT_EQUAL_MESSAGE("Image Diagnostics should calculate 18 features.", std::size_t(93), featureList.size());
 
     // These values are obtained with IBSI (3D Comb)
     // Standard accuracy is 0.01
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Joint Maximum with Large IBSI Phantom Image", 0.509, results["Co-occurenced Based Features::Overall Joint Maximum"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Joint Average with Large IBSI Phantom Image", 2.149, results["Co-occurenced Based Features::Overall Joint Average"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Joint Variance with Large IBSI Phantom Image", 3.132, results["Co-occurenced Based Features::Overall Joint Variance"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Joint Entropy with Large IBSI Phantom Image", 2.574, results["Co-occurenced Based Features::Overall Joint Entropy"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Difference Average with Large IBSI Phantom Image", 1.379, results["Co-occurenced Based Features::Overall Difference Average"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Difference Variance with Large IBSI Phantom Image", 3.215, results["Co-occurenced Based Features::Overall Difference Variance"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Difference Entropy with Large IBSI Phantom Image", 1.641, results["Co-occurenced Based Features::Overall Difference Entropy"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Sum Average with Large IBSI Phantom Image", 4.298, results["Co-occurenced Based Features::Overall Sum Average"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Sum Variance with Large IBSI Phantom Image", 7.412, results["Co-occurenced Based Features::Overall Sum Variance"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Sum Entropy with Large IBSI Phantom Image", 2.110, results["Co-occurenced Based Features::Overall Sum Entropy"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Angular Second Moment with Large IBSI Phantom Image", 0.291, results["Co-occurenced Based Features::Overall Angular Second Moment"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Contrast with Large IBSI Phantom Image", 5.118, results["Co-occurenced Based Features::Overall Contrast"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Dissimilarity with Large IBSI Phantom Image", 1.380, results["Co-occurenced Based Features::Overall Dissimilarity"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Inverse Difference with Large IBSI Phantom Image", 0.688, results["Co-occurenced Based Features::Overall Inverse Difference"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Inverse Difference Normalized with Large IBSI Phantom Image", 0.856, results["Co-occurenced Based Features::Overall Inverse Difference Normalized"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Inverse Difference Moment with Large IBSI Phantom Image", 0.631, results["Co-occurenced Based Features::Overall Inverse Difference Moment"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Inverse Difference Moment Normalized with Large IBSI Phantom Image", 0.902, results["Co-occurenced Based Features::Overall Inverse Difference Moment Normalized"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Inverse Variance with Large IBSI Phantom Image", 0.057, results["Co-occurenced Based Features::Overall Inverse Variance"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Correlation with Large IBSI Phantom Image", 0.183, results["Co-occurenced Based Features::Overall Correlation"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Autocorrelation with Large IBSI Phantom Image", 5.192, results["Co-occurenced Based Features::Overall Autocorrelation"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Cluster Tendency with Large IBSI Phantom Image", 7.412, results["Co-occurenced Based Features::Overall Cluster Tendency"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Cluster Shade with Large IBSI Phantom Image", 17.419, results["Co-occurenced Based Features::Overall Cluster Shade"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Cluster Prominence with Large IBSI Phantom Image", 147.464, results["Co-occurenced Based Features::Overall Cluster Prominence"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall First Measure of Information Correlation with Large IBSI Phantom Image", -0.0288, results["Co-occurenced Based Features::Overall First Measure of Information Correlation"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Second Measure of Information Correlation with Large IBSI Phantom Image", 0.269, results["Co-occurenced Based Features::Overall Second Measure of Information Correlation"], 0.001);
 
     // These values are obtained by manually running the tool
     // Values might be wrong.
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Row Maximum with Large IBSI Phantom Image", 0.679, results["Co-occurenced Based Features::Overall Row Maximum"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Row Average with Large IBSI Phantom Image", 2.149, results["Co-occurenced Based Features::Overall Row Average"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Row Variance with Large IBSI Phantom Image", 3.132, results["Co-occurenced Based Features::Overall Row Variance"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Row Entropy with Large IBSI Phantom Image", 1.306, results["Co-occurenced Based Features::Overall Row Entropy"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall First Row-Column Entropy with Large IBSI Phantom Image", 2.611, results["Co-occurenced Based Features::Overall First Row-Column Entropy"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Overall Second Row-Column Entropy with Large IBSI Phantom Image", 2.611, results["Co-occurenced Based Features::Overall Second Row-Column Entropy"], 0.001);
+
+
+
+
+    // These values are obtained with IBSI (3D Avg)
+    // Standard accuracy is 0.01
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Joint Maximum with Large IBSI Phantom Image", 0.503, results["Co-occurenced Based Features::Mean Joint Maximum"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Joint Average with Large IBSI Phantom Image", 2.143, results["Co-occurenced Based Features::Mean Joint Average"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Joint Variance with Large IBSI Phantom Image", 3.099, results["Co-occurenced Based Features::Mean Joint Variance"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Joint Entropy with Large IBSI Phantom Image", 2.399, results["Co-occurenced Based Features::Mean Joint Entropy"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Difference Average with Large IBSI Phantom Image", 1.431, results["Co-occurenced Based Features::Mean Difference Average"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Difference Variance with Large IBSI Phantom Image", 3.056, results["Co-occurenced Based Features::Mean Difference Variance"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Difference Entropy with Large IBSI Phantom Image", 1.563, results["Co-occurenced Based Features::Mean Difference Entropy"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Sum Average with Large IBSI Phantom Image", 4.2859, results["Co-occurenced Based Features::Mean Sum Average"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Sum Variance with Large IBSI Phantom Image", 7.072, results["Co-occurenced Based Features::Mean Sum Variance"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Sum Entropy with Large IBSI Phantom Image", 1.9226, results["Co-occurenced Based Features::Mean Sum Entropy"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Angular Second Moment with Large IBSI Phantom Image", 0.303, results["Co-occurenced Based Features::Mean Angular Second Moment"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Contrast with Large IBSI Phantom Image", 5.3245, results["Co-occurenced Based Features::Mean Contrast"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Dissimilarity with Large IBSI Phantom Image", 1.431, results["Co-occurenced Based Features::Mean Dissimilarity"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Inverse Difference with Large IBSI Phantom Image", 0.6766, results["Co-occurenced Based Features::Mean Inverse Difference"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Inverse Difference Normalized with Large IBSI Phantom Image", 0.8506, results["Co-occurenced Based Features::Mean Inverse Difference Normalized"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Inverse Difference Moment with Large IBSI Phantom Image", 0.6177, results["Co-occurenced Based Features::Mean Inverse Difference Moment"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Inverse Difference Moment Normalized with Large IBSI Phantom Image", 0.8984, results["Co-occurenced Based Features::Mean Inverse Difference Moment Normalized"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Inverse Variance with Large IBSI Phantom Image", 0.0604, results["Co-occurenced Based Features::Mean Inverse Variance"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Correlation with Large IBSI Phantom Image", 0.157, results["Co-occurenced Based Features::Mean Correlation"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Autocorrelation with Large IBSI Phantom Image", 5.05544, results["Co-occurenced Based Features::Mean Autocorrelation"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Cluster Tendency with Large IBSI Phantom Image", 7.0728, results["Co-occurenced Based Features::Mean Cluster Tendency"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Cluster Shade with Large IBSI Phantom Image", 16.6441, results["Co-occurenced Based Features::Mean Cluster Shade"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Cluster Prominence with Large IBSI Phantom Image", 144.703, results["Co-occurenced Based Features::Mean Cluster Prominence"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean First Measure of Information Correlation with Large IBSI Phantom Image", -0.15684, results["Co-occurenced Based Features::Mean First Measure of Information Correlation"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Second Measure of Information Correlation with Large IBSI Phantom Image", 0.519588, results["Co-occurenced Based Features::Mean Second Measure of Information Correlation"], 0.001);
+
+    // These values are obtained by manually running the tool
+    // Values might be wrong.
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Row Maximum with Large IBSI Phantom Image", 0.6808, results["Co-occurenced Based Features::Mean Row Maximum"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Row Average with Large IBSI Phantom Image", 2.143, results["Co-occurenced Based Features::Mean Row Average"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Row Variance with Large IBSI Phantom Image", 3.0993, results["Co-occurenced Based Features::Mean Row Variance"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Row Entropy with Large IBSI Phantom Image", 1.29699, results["Co-occurenced Based Features::Mean Row Entropy"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean First Row-Column Entropy with Large IBSI Phantom Image", 2.5939, results["Co-occurenced Based Features::Mean First Row-Column Entropy"], 0.001);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("Co-occurenced Based Features::Mean Second Row-Column Entropy with Large IBSI Phantom Image", 2.5939, results["Co-occurenced Based Features::Mean Second Row-Column Entropy"], 0.001);
   }
 
   void ImageDescription_PhantomTest_2D()
   {
     mitk::GIFCooccurenceMatrix2::Pointer featureCalculator = mitk::GIFCooccurenceMatrix2::New();
 
     featureCalculator->SetUseBinsize(true);
     featureCalculator->SetBinsize(1.0);
     featureCalculator->SetUseMinimumIntensity(true);
     featureCalculator->SetUseMaximumIntensity(true);
     featureCalculator->SetMinimumIntensity(0.5);
     featureCalculator->SetMaximumIntensity(6.5);
 
     auto featureList = featureCalculator->CalculateFeaturesSlicewise(m_IBSI_Phantom_Image_Large, m_IBSI_Phantom_Mask_Large, 2);
 
     std::map<std::string, double> results;
     for (auto valuePair : featureList)
     {
       MITK_INFO << valuePair.first << " : " << valuePair.second;
       results[valuePair.first] = valuePair.second;
     }
     CPPUNIT_ASSERT_EQUAL_MESSAGE("Image Diagnostics should calculate 108 features.", std::size_t(108), featureList.size());
 
     // These values are obtained with IBSI
     // Standard accuracy is 0.01
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Small Zone Emphasis with Large IBSI Phantom Image", 0.363, results["SliceWise Mean Grey Level Size Zone::Small Zone Emphasis"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Large Zone Emphasis with Large IBSI Phantom Image", 43.9, results["SliceWise Mean Grey Level Size Zone::Large Zone Emphasis"], 0.1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Low Grey Level Emphasis with Large IBSI Phantom Image", 0.371, results["SliceWise Mean Grey Level Size Zone::Low Grey Level Emphasis"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::High Grey Level Emphasis with Large IBSI Phantom Image", 16.4, results["SliceWise Mean Grey Level Size Zone::High Grey Level Emphasis"], 0.1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Small Zone Low Grey Level Emphasis with Large IBSI Phantom Image", 0.0259, results["SliceWise Mean Grey Level Size Zone::Small Zone Low Grey Level Emphasis"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Small Zone High Grey Level Emphasis with Large IBSI Phantom Image", 10.3, results["SliceWise Mean Grey Level Size Zone::Small Zone High Grey Level Emphasis"], 0.1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Large Zone Low Grey Level Emphasis with Large IBSI Phantom Image", 40.4, results["SliceWise Mean Grey Level Size Zone::Large Zone Low Grey Level Emphasis"], 1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Large Zone High Grey Level Emphasis with Large IBSI Phantom Image", 113, results["SliceWise Mean Grey Level Size Zone::Large Zone High Grey Level Emphasis"], 1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Grey Level Non-Uniformity with Large IBSI Phantom Image", 1.41, results["SliceWise Mean Grey Level Size Zone::Grey Level Non-Uniformity"], 0.01);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Grey Level Non-Uniformity Normalized with Large IBSI Phantom Image", 0.323, results["SliceWise Mean Grey Level Size Zone::Grey Level Non-Uniformity Normalized"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Size Non-Uniformity with Large IBSI Phantom Image", 1.49, results["SliceWise Mean Grey Level Size Zone::Zone Size Non-Uniformity"], 0.1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Size Non-Uniformity Normalized with Large IBSI Phantom Image", 0.333, results["SliceWise Mean Grey Level Size Zone::Zone Size Non-Uniformity Normalized"], 0.01);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Percentage with Large IBSI Phantom Image", 0.24, results["SliceWise Mean Grey Level Size Zone::Zone Percentage"], 0.01);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Grey Level Variance with Large IBSI Phantom Image", 3.97, results["SliceWise Mean Grey Level Size Zone::Grey Level Variance"], 0.01);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Size Variance with Large IBSI Phantom Image", 21, results["SliceWise Mean Grey Level Size Zone::Zone Size Variance"], 0.1);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Size Entropy with Large IBSI Phantom Image", 1.93, results["SliceWise Mean Grey Level Size Zone::Zone Size Entropy"], 0.01);
     //CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone:: with Large IBSI Phantom Image", 0.045, results["SliceWise Mean Grey Level Size Zone::"], 0.001);
 
     // These values are obtained by manually running the tool
     // Values might be wrong.
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Grey Level Mean with Large IBSI Phantom Image", 3.526, results["SliceWise Mean Grey Level Size Zone::Grey Level Mean"], 0.001);
     CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("SliceWise Mean Grey Level Size Zone::Zone Size Mean with Large IBSI Phantom Image", 4.59524, results["SliceWise Mean Grey Level Size Zone::Zone Size Mean"], 0.001);
   }
 
 };
 
 MITK_TEST_SUITE_REGISTRATION(mitkGIFCooc2 )
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