diff --git a/Modules/Classification/CLUtilities/test/mitkGIFFirstOrderNumericStatisticsTest.cpp b/Modules/Classification/CLUtilities/test/mitkGIFFirstOrderNumericStatisticsTest.cpp
index e9618cb237..c392384b01 100644
--- a/Modules/Classification/CLUtilities/test/mitkGIFFirstOrderNumericStatisticsTest.cpp
+++ b/Modules/Classification/CLUtilities/test/mitkGIFFirstOrderNumericStatisticsTest.cpp
@@ -1,82 +1,113 @@
 /*===================================================================
 
 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 <mitkGIFFirstOrderNumericStatistics.h>
 
 class mitkGIFFirstOrderNumericStatisticsTestSuite : public mitk::TestFixture
 {
   CPPUNIT_TEST_SUITE(mitkGIFFirstOrderNumericStatisticsTestSuite);
 
   MITK_TEST(ImageDescription_PhantomTest);
 
   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()
   {
     mitk::GIFFirstOrderNumericStatistics::Pointer featureCalculator = mitk::GIFFirstOrderNumericStatistics::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 46 features.", std::size_t(46), featureList.size());
+    CPPUNIT_ASSERT_EQUAL_MESSAGE("Image Diagnostics should calculate 50 features.", std::size_t(50), featureList.size());
 
     // These values are obtained by a run of the filter.
     // The might be wrong!
-    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Histogram::Mean Value should be 2.15 with Large IBSI Phantom Image", 2.15, results["First Order Histogram::Mean Value"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Mean with Large IBSI Phantom Image", 2.15, results["First Order Numeric::Mean"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Variance with Large IBSI Phantom Image", 3.05, results["First Order Numeric::Variance"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Skewness with Large IBSI Phantom Image", 1.08, results["First Order Numeric::Skewness"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Excess kurtosis with Large IBSI Phantom Image", -0.355, results["First Order Numeric::Excess kurtosis"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Median with Large IBSI Phantom Image", 1, results["First Order Numeric::Median"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Minimum with Large IBSI Phantom Image", 1, results["First Order Numeric::Minimum"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::10th Percentile with Large IBSI Phantom Image", 1, results["First Order Numeric::10th Percentile"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::90th Percentile with Large IBSI Phantom Image", 4, results["First Order Numeric::90th Percentile"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Maximum with Large IBSI Phantom Image", 6, results["First Order Numeric::Maximum"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Interquantile range with Large IBSI Phantom Image", 3, results["First Order Numeric::Interquantile range"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Range with Large IBSI Phantom Image", 5, results["First Order Numeric::Range"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Mean absolute deviation with Large IBSI Phantom Image", 1.55, results["First Order Numeric::Mean absolute deviation"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Robust mean absolute deviation with Large IBSI Phantom Image", 1.11, results["First Order Numeric::Robust mean absolute deviation"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Median absolute deviation with Large IBSI Phantom Image", 1.15, results["First Order Numeric::Median absolute deviation"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Coefficient of variation with Large IBSI Phantom Image", 0.812, results["First Order Numeric::Coefficient of variation"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Quantile coefficient of dispersion with Large IBSI Phantom Image", 0.6, results["First Order Numeric::Quantile coefficient of dispersion"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Energy with Large IBSI Phantom Image", 567, results["First Order Numeric::Energy"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Root mean square with Large IBSI Phantom Image", 2.77, results["First Order Numeric::Root mean square"], 0.01);
 
 
     // These values are taken from the IBSI Initiative to ensure compatibility
     // The values are given with an accuracy of 0.01
-    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Histogram::Mean Index should be 2.15 with Large IBSI Phantom Image", 2.15, results["First Order Histogram::Mean Index"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Standard Deviation with Large IBSI Phantom Image", 1.74513, results["First Order Numeric::Standard Deviation"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Kurtosis with Large IBSI Phantom Image", 2.64538, results["First Order Numeric::Kurtosis"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Robust mean with Large IBSI Phantom Image", 1.74627, results["First Order Numeric::Robust mean"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Robust variance with Large IBSI Phantom Image", 1.65204, results["First Order Numeric::Robust variance"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Covered image intensity range with Large IBSI Phantom Image", 1.2, results["First Order Numeric::Covered image intensity range"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Mode index with Large IBSI Phantom Image",0 , results["First Order Numeric::Mode index"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Mode value with Large IBSI Phantom Image", 1, results["First Order Numeric::Mode value"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Mode probability with Large IBSI Phantom Image", 0.675676, results["First Order Numeric::Mode probability"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Entropy with Large IBSI Phantom Image", -1.26561, results["First Order Numeric::Entropy"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Uniformtiy with Large IBSI Phantom Image", 0.512418, results["First Order Numeric::Uniformtiy"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Number of voxels with Large IBSI Phantom Image", 74 , results["First Order Numeric::Number of voxels"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Sum of voxels with Large IBSI Phantom Image", 159, results["First Order Numeric::Sum of voxels"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Voxel space with Large IBSI Phantom Image", 8, results["First Order Numeric::Voxel space"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Voxel volume with Large IBSI Phantom Image", 8, results["First Order Numeric::Voxel volume"], 0.01);
+    CPPUNIT_ASSERT_DOUBLES_EQUAL_MESSAGE("First Order Numeric::Image Dimension with Large IBSI Phantom Image", 3, results["First Order Numeric::Image Dimension"], 0.01);
 
   }
 
 };
 
 MITK_TEST_SUITE_REGISTRATION(mitkGIFFirstOrderNumericStatistics )
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