diff --git a/Plugins/org.mitk.gui.qt.activelearning/src/internal/QmitkActiveLearning.cpp b/Plugins/org.mitk.gui.qt.activelearning/src/internal/QmitkActiveLearning.cpp
index d3f2c8a787..1f164fa1d5 100644
--- a/Plugins/org.mitk.gui.qt.activelearning/src/internal/QmitkActiveLearning.cpp
+++ b/Plugins/org.mitk.gui.qt.activelearning/src/internal/QmitkActiveLearning.cpp
@@ -1,733 +1,792 @@
 /*===================================================================
 
 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.
 
 ===================================================================*/
 
 // Blueberry
 #include <berryISelectionService.h>
 #include <berryIWorkbenchWindow.h>
 
 // Qt
 #include <QColorDialog>
 #include <QMessageBox>
 #include <QFuture>
 #include <QtConcurrent>
 
 // Qmitk
 #include "QmitkActiveLearning.h"
 #include <QmitkLabelSetWidget.h>
 
 // MITK
 #include <usModuleRegistry.h>
 #include <mitkImage.h>
 #include <mitkImageWriteAccessor.h>
 #include <mitkLabel.h>
 #include <mitkBaseGeometry.h>
 #include <mitkNumericTypes.h>
 #include <mitkPixelType.h>
 #include <mitkImageCast.h>
 #include <mitkImageAccessByItk.h>
 
 // ITK
 #include <itkDiscreteGaussianImageFilter.h>
 #include <itkGradientMagnitudeRecursiveGaussianImageFilter.h>
 #include <itkLaplacianRecursiveGaussianImageFilter.h>
 #include <itkHessianMatrixEigenvalueImageFilter.h>
 #include <itkStructureTensorEigenvalueImageFilter.h>
-
+#include <itkHessianRecursiveGaussianImageFilter.h>
+#include <itkSymmetricEigenAnalysisImageFilter.h>
+#include <itkImageRegionIterator.h>
 
 // Returns true if list has at least one entry and all entries are valid mitk::Images, otherwise false
 static bool SelectionAllImages(const QList<mitk::DataNode::Pointer>& nodes)
 {
     if (nodes.empty())
     {
         return false;
     }
     for (const auto& node : nodes)
     {
         if(!(node.IsNotNull() && dynamic_cast<mitk::Image*>(node->GetData()) != nullptr)) return false;
     }
     return true;
 }
 
 // QColor to mitk::Color
 static mitk::Color QColorToMitkColor(const QColor& qcolor)
 {
     mitk::Color color;
     color.SetRed((float)qcolor.red() / 255);
     color.SetGreen((float)qcolor.green() / 255);
     color.SetBlue((float)qcolor.blue() / 255);
     return color;
 }
 
 // For debugging
 static void PrintAllLabels(mitk::LabelSetImage* image)
 {
     for (auto it=image->GetActiveLabelSet()->IteratorBegin(); it!=image->GetActiveLabelSet()->IteratorConstEnd(); ++it)
     {
         MITK_INFO << "Key: " << it->first << " - Name: " << it->second->GetName() << " - Value: " << it->second->GetValue() << " - Color: " << it->second->GetColor();
     }
 }
 
 // Make values of labels a consistent range
 static void FillLabelValues(mitk::LabelSetImage* image)
 {
     int value(0);
     for (auto it=image->GetActiveLabelSet()->IteratorBegin(); it!=image->GetActiveLabelSet()->IteratorConstEnd(); ++it)
     {
         it->second->SetValue(value);
         value++;
     }
     image->GetActiveLabelSet()->SetActiveLabel(0);
 }
 
 // Fill image with zeros
 static void FillWithZeros(mitk::Image* image)
 {
     unsigned int size = image->GetPixelType().GetSize();
     for (unsigned int i=0; i<image->GetDimension(); i++)
     {
         size *= image->GetDimension(i);
     }
     for (unsigned int t=0; t<image->GetTimeSteps(); t++)
     {
         mitk::ImageWriteAccessor accessor(image, image->GetVolumeData(0));
         memset(accessor.GetData(), 0, size);
     }
 }
 
 /* ==================================================================
  * FEATURES
  * =============================================================== */
 
 template<typename PixelType, unsigned int imageDimension>
 static void GaussianSmoothing(const itk::Image<PixelType, imageDimension>* inputImage, float sigma, mitk::Image::Pointer outputImage)
 {
     typedef itk::Image<PixelType, imageDimension> ImageType;
     auto filter = itk::DiscreteGaussianImageFilter<ImageType, ImageType>::New();
     filter->SetInput(inputImage);
     filter->SetVariance(sigma*sigma);
     filter->Update();
     mitk::GrabItkImageMemory(filter->GetOutput(), outputImage);
 }
 
 template<typename PixelType, unsigned int imageDimension>
 static void GaussianGradientMagnitude(const itk::Image<PixelType, imageDimension>* inputImage, float sigma, mitk::Image::Pointer outputImage)
 {
     typedef itk::Image<PixelType, imageDimension> ImageType;
-    auto filter = itk::GradientMagnitudeRecursiveGaussianImageFilter<ImageType, ImageType>::New();
+    auto filter = itk::GradientMagnitudeRecursiveGaussianImageFilter<ImageType>::New();
     filter->SetInput(inputImage);
     filter->SetSigma(sigma);
     filter->Update();
     mitk::GrabItkImageMemory(filter->GetOutput(), outputImage);
 }
 
 template<typename PixelType, unsigned int imageDimension>
 static void LaplacianOfGaussian(const itk::Image<PixelType, imageDimension>* inputImage, float sigma, mitk::Image::Pointer outputImage)
 {
     typedef itk::Image<PixelType, imageDimension> ImageType;
-    auto filter = itk::LaplacianRecursiveGaussianImageFilter<ImageType, ImageType>::New();
+    auto filter = itk::LaplacianRecursiveGaussianImageFilter<ImageType>::New();
     filter->SetInput(inputImage);
     filter->SetSigma(sigma);
     filter->Update();
     mitk::GrabItkImageMemory(filter->GetOutput(), outputImage);
 }
 
 template<typename PixelType, unsigned int imageDimension>
 static void StructureTensorEigenvalues(const itk::Image<PixelType, imageDimension>* inputImage, float sigma, std::vector<mitk::Image::Pointer> outputImages)
 {
     typedef itk::Image<PixelType, imageDimension> ImageType;
     auto filter = itk::StructureTensorEigenvalueImageFilter<ImageType>::New();
     filter->SetInput(inputImage);
     filter->SetInnerScale(sigma);
     filter->SetOuterScale(sigma);
     filter->Update();
     for (unsigned int i=0; i<filter->GetNumberOfOutputs(); i++)
     {
         mitk::GrabItkImageMemory(filter->GetOutput(i), outputImages[i]);
     }
 }
 
 template<typename PixelType, unsigned int imageDimension>
 static void HessianEigenvalues(const itk::Image<PixelType, imageDimension>* inputImage, float sigma, std::vector<mitk::Image::Pointer> outputImages)
 {
     typedef itk::Image<PixelType, imageDimension> ImageType;
-    auto filter = itk::HessianMatrixEigenvalueImageFilter<ImageType>::New();
+    typedef itk::Image<itk::SymmetricSecondRankTensor<PixelType, imageDimension>, imageDimension> TensorImageType;
+    auto filter = itk::HessianRecursiveGaussianImageFilter<ImageType, TensorImageType>::New();
+
+    ImageType::Pointer o1, o2, o3;
+    o1->Allocate();
+    o2->Allocate();
+    o3->Allocate();
+
     filter->SetInput(inputImage);
     filter->SetSigma(sigma);
     filter->Update();
+    TensorImageType::Pointer tensorImage = filter->GetOutput();
+
+    itk::ImageRegionIterator<TensorImageType> tensorIt(tensorImage, tensorImage->GetLargestPossibleRegion());
+    itk::ImageRegionIterator<ImageType> o1It(o1, o1->GetLargestPossibleRegion());
+    itk::ImageRegionIterator<ImageType> o2It(o2, o2->GetLargestPossibleRegion());
+    itk::ImageRegionIterator<ImageType> o3It(o3, o3->GetLargestPossibleRegion());
+
+    while (!tensorIt.IsAtEnd())
+    {
+	itk::SymmetricSecondRankTensor<PixelType, imageDimension>::EigenValue
+
     for (unsigned int i=0; i<filter->GetNumberOfOutputs(); i++)
     {
         mitk::GrabItkImageMemory(filter->GetOutput(i), outputImages[i]);
     }
 }
 
 /* ==================================================================
  * PUBLIC SLOTS
  * =============================================================== */
 
 
 void ActiveLearning::Initialize()
 {
     // Get selected nodes and check again if these are all images
     m_Nodes = this->GetDataManagerSelection();
     if (!SelectionAllImages(m_Nodes)) return;
 
     m_Controls.m_InitializePushButton->setDisabled(true);
 
     // Set names to the label (again)
     QString nameList = QString::fromStdString(m_Nodes[0]->GetName());
     if (m_Nodes.length() >= 2)
     {
         for (int i=1; i<m_Nodes.length(); ++i)
         {
             nameList += QString("<br />");
             nameList += QString::fromStdString(m_Nodes[i]->GetName());
         }
     }
     m_Controls.m_InitializeLabel->setText(nameList);
 
     // =======================================
     // ANNOTATION IMAGE
     // =======================================
 
     m_AnnotationImage = mitk::LabelSetImage::New();
 
     try
     {
         auto referenceImage = dynamic_cast<mitk::Image*>(m_Nodes[0]->GetData());
         m_AnnotationImage->Initialize(referenceImage);
     }
     catch (mitk::Exception& e)
     {
         MITK_ERROR << "Exception caught: " << e.GetDescription();
         QMessageBox::information(m_Parent, "Error", "Could not initialize annotation image");
         return;
     }
 
     FillWithZeros(m_AnnotationImage);
 
     m_AnnotationNode = mitk::DataNode::New();
     m_AnnotationNode->SetData(m_AnnotationImage);
     m_AnnotationNode->SetName("Labels");
     m_AnnotationNode->SetColor(1., 1., 1.);
 //    m_AnnotationNode->SetBoolProperty("helper object", true);
     m_AnnotationImage->GetExteriorLabel()->SetProperty("name.parent", mitk::StringProperty::New(m_Nodes[0]->GetName().c_str()));
     m_AnnotationImage->GetExteriorLabel()->SetProperty("name.image", mitk::StringProperty::New("Labels"));
     this->GetDataStorage()->Add(m_AnnotationNode, m_Nodes[0]);
 
     // =======================================
     // PREDICTION IMAGE
     // =======================================
 
     m_PredictionImage = mitk::Image::New();
 
     try
     {
         mitk::Image::Pointer referenceImage = dynamic_cast<mitk::Image*>(m_Nodes[0]->GetData());
         m_PredictionImage->Initialize(referenceImage);
     }
     catch (mitk::Exception& e)
     {
         MITK_ERROR << "Exception caught: " << e.GetDescription();
         QMessageBox::information(m_Parent, "Error", "Could not initialize prediction image");
         return;
     }
 
     FillWithZeros(m_PredictionImage);
 
     m_PredictionNode = mitk::DataNode::New();
     m_PredictionNode->SetData(m_PredictionImage);
     m_PredictionNode->SetName("Predictions");
     m_PredictionNode->SetColor(1., 1., 1.);
 //    m_PredictionNode->SetBoolProperty("helper object", true);
 //    m_PredictionImage->GetExteriorLabel()->SetProperty("name.parent", mitk::StringProperty::New(nodes[0]->GetName().c_str()));
 //    m_PredictionImage->GetExteriorLabel()->SetProperty("name.image", mitk::StringProperty::New("Predictions"));
     this->GetDataStorage()->Add(m_PredictionNode, m_Nodes[0]);
 
     // =======================================
     // SEGMENTATION IMAGE
     // =======================================
 
     m_SegmentationImage = mitk::LabelSetImage::New();
 
     try
     {
         auto referenceImage = dynamic_cast<mitk::Image*>(m_Nodes[0]->GetData());
         m_SegmentationImage->Initialize(referenceImage);
     }
     catch (mitk::Exception& e)
     {
         MITK_ERROR << "Exception caught: " << e.GetDescription();
         QMessageBox::information(m_Parent, "Error", "Could not initialize segmentation image");
         return;
     }
 
     FillWithZeros(m_SegmentationImage);
 
     m_SegmentationNode = mitk::DataNode::New();
     m_SegmentationNode->SetData(m_SegmentationImage);
     m_SegmentationNode->SetName("Segmentation");
     m_SegmentationNode->SetColor(1., 1., 1.);
 //    m_PredictionNode->SetBoolProperty("helper object", true);
     m_SegmentationImage->GetExteriorLabel()->SetProperty("name.parent", mitk::StringProperty::New(m_Nodes[0]->GetName().c_str()));
     m_SegmentationImage->GetExteriorLabel()->SetProperty("name.image", mitk::StringProperty::New("Segmentation"));
     this->GetDataStorage()->Add(m_SegmentationNode, m_Nodes[0]);
 
     // Calculate features
     for (const auto node : m_Nodes)
     {
         mitk::Image::Pointer currentImage = dynamic_cast<mitk::Image*>(node->GetData());
         QFuture<std::vector<std::pair<mitk::Image::Pointer, std::string>>> future;
         future = QtConcurrent::run(this, &ActiveLearning::CalculateFeatures, currentImage);
         auto futureWatcher = new QFutureWatcher<std::vector<std::pair<mitk::Image::Pointer, std::string>>>();
         futureWatcher->setFuture(future);
         connect(futureWatcher, SIGNAL(finished()), this, SLOT(OnInitializationFinished()));
         m_FeatureCalculationWatchers.push_back(futureWatcher);
     }
 
     // Interactor
     auto activeLearningLib = us::ModuleRegistry::GetModule("MitkCLActiveLearning");
     m_Interactor = mitk::ActiveLearningInteractor::New();
     m_Interactor->LoadStateMachine("Paint.xml", activeLearningLib);
     m_Interactor->SetEventConfig("PaintConfig.xml", activeLearningLib);
     m_Interactor->SetDataNode(m_AnnotationNode);
 
     // Automatically add first label
     OnAddLabelPushButtonClicked();
 
-    m_Controls.m_LabelControlsFrame->setVisible(true);
-    m_Controls.m_InitializePushButton->setHidden(true);
-
     m_Active = true;
 }
 
 
 /* ==================================================================
  * PUBLIC
  * =============================================================== */
 
 
 ActiveLearning::ActiveLearning() :
     m_Parent(nullptr),
     m_AnnotationImage(nullptr),
     m_AnnotationNode(nullptr),
     m_PredictionImage(nullptr),
     m_PredictionNode(nullptr),
     m_SegmentationImage(nullptr),
     m_SegmentationNode(nullptr),
     m_Active(false)
 {
 
 }
 
 ActiveLearning::~ActiveLearning()
 {
 
 }
 
 void ActiveLearning::CreateQtPartControl( QWidget *parent )
 {
     m_Controls.setupUi(parent);
     m_Parent = parent;
 
     // Label model
     m_LabelListModel = new QStandardItemModel(0, 3, this);
     m_Controls.m_LabelTableView->setModel(m_LabelListModel);
     m_Controls.m_LabelTableView->horizontalHeader()->setDefaultSectionSize(20);
     m_Controls.m_LabelTableView->verticalHeader()->setDefaultSectionSize(20);
     NotEditableDelegate* itemDelegate = new NotEditableDelegate(parent);
     m_Controls.m_LabelTableView->setItemDelegateForColumn(1, itemDelegate);
     connect(m_Controls.m_LabelTableView, SIGNAL(doubleClicked(QModelIndex)),
             this, SLOT(OnColorIconDoubleClicked(QModelIndex)));
     connect(m_Controls.m_LabelTableView->selectionModel(), SIGNAL(selectionChanged(QItemSelection, QItemSelection)),
             this, SLOT(OnLabelListSelectionChanged(QItemSelection, QItemSelection)));
     connect(m_LabelListModel, SIGNAL(dataChanged(QModelIndex, QModelIndex)),
             this, SLOT(OnLabelNameChanged(QModelIndex, QModelIndex)));
 
     // Buttons
     connect(m_Controls.m_InitializePushButton, SIGNAL(clicked()),
             this, SLOT(Initialize()));
     connect(m_Controls.m_AddLabelPushButton, SIGNAL(clicked()),
             this, SLOT(OnAddLabelPushButtonClicked()));
     connect(m_Controls.m_RemoveLabelPushButton, SIGNAL(clicked()),
             this, SLOT(OnRemoveLabelPushButtonClicked()));
     connect(m_Controls.m_PaintToolButton, SIGNAL(clicked()),
             this, SLOT(OnPaintToolButtonClicked()));
     connect(m_Controls.m_EraseToolButton, SIGNAL(clicked()),
             this, SLOT(OnEraseToolButtonClicked()));
 
     // Set start configuration
     m_Controls.m_LabelControlsFrame->setVisible(false);
     SetInitializeReady(false);
 }
 
 void ActiveLearning::ResetLabels()
 {
     // Remove all labels but the first
     for (auto it=m_AnnotationImage->GetActiveLabelSet()->IteratorBegin(); it!=m_AnnotationImage->GetActiveLabelSet()->IteratorConstEnd(); it++)
     {
         if (it->first != 0)
         {
             m_AnnotationImage->GetActiveLabelSet()->RemoveLabel(it->first);
         }
     }
 
     // Fill with labels from list
     for (int i=0; i<m_LabelListModel->rowCount(); i++)
     {
         QString name = m_LabelListModel->item(i, 2)->text();
         m_LabelListModel->item(i, 1)->setText(QString::number(i + 1));
         QColor color = m_LabelListModel->item(i)->background().color();
         m_AnnotationImage->GetActiveLabelSet()->AddLabel(name.toStdString(), QColorToMitkColor(color));
     }
 }
 
 std::vector<std::pair<mitk::Image::Pointer, std::string> > ActiveLearning::CalculateFeatures(const mitk::Image::Pointer inputImage)
 {
     std::vector<std::pair<mitk::Image::Pointer, std::string>> result;
 
     // TODO: Get features from preference page
     std::vector<float> sigmas = {0.7, 1.6};
 
     for (auto sigma : sigmas)
     {
         std::stringstream ss;
 
         auto gaussImage = mitk::Image::New();
         AccessByItk_n(inputImage, GaussianSmoothing, (sigma, gaussImage));
         ss << "GaussianSmoothing (" << std::fixed << std::setprecision(2) << sigma << ")";
         result.push_back(std::pair<mitk::Image::Pointer, std::string>(gaussImage, ss.str()));
         ss.str("");
 
         auto gradMagImage = mitk::Image::New();
         AccessByItk_n(inputImage, GaussianGradientMagnitude, (sigma, gradMagImage));
         ss << "GaussianGradientMagnitude (" << std::fixed << std::setprecision(2) << sigma << ")";
         result.push_back(std::pair<mitk::Image::Pointer, std::string>(gradMagImage, ss.str()));
         ss.str("");
+
+        auto logImage = mitk::Image::New();
+        AccessByItk_n(inputImage, LaplacianOfGaussian, (sigma, logImage));
+        ss << "LaplacianOfGaussian (" << std::fixed << std::setprecision(2) << sigma << ")";
+        result.push_back(std::pair<mitk::Image::Pointer, std::string>(logImage, ss.str()));
+        ss.str("");
+
+//        auto structImage1 = mitk::Image::New();
+//        auto structImage2 = mitk::Image::New();
+//        auto structImage3 = mitk::Image::New();
+//        std::vector<mitk::Image::Pointer> structImages = {structImage1, structImage2, structImage3};
+//        AccessByItk_n(inputImage, StructureTensorEigenvalues, (sigma, structImages));
+//        ss << "StructureTensorEigenvalue1 (" << std::fixed << std::setprecision(2) << sigma << ")";
+//        result.push_back(std::pair<mitk::Image::Pointer, std::string>(structImage1, ss.str()));
+//        ss.str("");
+//        ss << "StructureTensorEigenvalue2 (" << std::fixed << std::setprecision(2) << sigma << ")";
+//        result.push_back(std::pair<mitk::Image::Pointer, std::string>(structImage2, ss.str()));
+//        ss.str("");
+//        if (inputImage->GetDimension() == 3)
+//        {
+//            ss << "StructureTensorEigenvalue3 (" << std::fixed << std::setprecision(2) << sigma << ")";
+//            result.push_back(std::pair<mitk::Image::Pointer, std::string>(structImage3, ss.str()));
+//            ss.str("");
+//        }
+
+        auto hessianImage1 = mitk::Image::New();
+        auto hessianImage2 = mitk::Image::New();
+        auto hessianImage3 = mitk::Image::New();
+        std::vector<mitk::Image::Pointer> hessianImages = {hessianImage1, hessianImage2, hessianImage3};
+        AccessByItk_n(inputImage, HessianEigenvalues, (sigma, hessianImages));
+        ss << "HessianEigenvalue1 (" << std::fixed << std::setprecision(2) << sigma << ")";
+        result.push_back(std::pair<mitk::Image::Pointer, std::string>(hessianImage1, ss.str()));
+        ss.str("");
+        ss << "HessianEigenvalue2 (" << std::fixed << std::setprecision(2) << sigma << ")";
+        result.push_back(std::pair<mitk::Image::Pointer, std::string>(hessianImage2, ss.str()));
+        ss.str("");
+        if (inputImage->GetDimension() == 3)
+        {
+            ss << "HessianEigenvalue3 (" << std::fixed << std::setprecision(2) << sigma << ")";
+            result.push_back(std::pair<mitk::Image::Pointer, std::string>(hessianImage3, ss.str()));
+            ss.str("");
+        }
     }
 
     return result;
 }
 
 const std::string ActiveLearning::VIEW_ID = "org.mitk.views.activelearning";
 
 
 /* ==================================================================
  * PROTECTED SLOTS
  * =============================================================== */
 
 
 void ActiveLearning::OnAddLabelPushButtonClicked()
 {
     QString labelName = QString("Label ") + QString::number(m_AnnotationImage->GetActiveLabelSet()->ReverseIteratorBegin()->first + 1);
     QColor labelColor = Qt::GlobalColor(m_LabelListModel->rowCount() % 12 + 7); // We only want Qt default colors 7 to 18
 
     // Create icon
     QStandardItem* colorSquare = new QStandardItem;
     colorSquare->setBackground(labelColor);
     colorSquare->setEditable(false);
     QPixmap colorPixmap(20, 20);
     colorPixmap.fill(labelColor);
     colorSquare->setIcon(QIcon(colorPixmap));
 
     // Key is the highest existing key + 1
     int value = (int)m_AnnotationImage->GetActiveLabelSet()->ReverseIteratorBegin()->first + 1;
     QStandardItem* valueItem = new QStandardItem();
     valueItem->setText(QString::number(value));
 
     // Create label item
     QStandardItem* label = new QStandardItem(labelName);
 
     // Add to image
     m_AnnotationImage->GetActiveLabelSet()->AddLabel(labelName.toStdString(), QColorToMitkColor(labelColor));
     PrintAllLabels(m_AnnotationImage);
 
     // Make list and insert
     QList<QStandardItem*> list;
     list.append(colorSquare);
     list.append(valueItem);
     list.append(label);
     m_LabelListModel->appendRow(list);
 
     // If this is the first label, we activate the paint button
     // We also have to set the data node color for this one, because for 1 values that color seems to define the rendered color
     if (m_LabelListModel->rowCount() == 1)
     {
         OnPaintToolButtonClicked();
         m_AnnotationNode->SetColor(QColorToMitkColor(labelColor));
     }
 
     // Select newly added label
     m_Controls.m_LabelTableView->selectRow(m_LabelListModel->rowCount() - 1);
 }
 
 void ActiveLearning::OnRemoveLabelPushButtonClicked()
 {
     QItemSelectionModel* selection = m_Controls.m_LabelTableView->selectionModel();
     if (selection->hasSelection())
     {
         unsigned int removeIndex = selection->selectedRows().first().row();
         QString removeMessage = QString("Remove label '") + m_LabelListModel->item(removeIndex, 2)->text() + QString("'?");
         QMessageBox::StandardButton removeReply;
         removeReply = QMessageBox::question(m_Parent,
                                             "Remove Label",
                                             removeMessage,
                                             QMessageBox::Yes | QMessageBox::No);
         if (removeReply == QMessageBox::Yes)
         {
             // if there are no annotations, reset labels
             if (m_Interactor->IsUsed())
             {
                 std::vector<mitk::LabelSetImage::PixelType> labels;
                 labels.push_back(m_LabelListModel->item(removeIndex, 1)->text().toInt());
                 m_AnnotationImage->RemoveLabels(labels);
                 m_LabelListModel->removeRow(removeIndex);
             }
             else
             {
                 m_LabelListModel->removeRow(removeIndex);
                 ResetLabels();
             }
             PrintAllLabels(m_AnnotationImage);
         }
     }
 }
 
 void ActiveLearning::OnPaintToolButtonClicked()
 {
     m_Controls.m_PaintToolButton->setChecked(true);
     QItemSelectionModel* selection = m_Controls.m_LabelTableView->selectionModel();
     int row(0);
     if (selection->hasSelection())
     {
         row = selection->selectedRows().first().row();
     }
     else
     {
         m_Controls.m_LabelTableView->selectRow(0);
     }
     m_Interactor->SetPaintingPixelValue(m_LabelListModel->item(row, 1)->text().toInt());
     m_AnnotationImage->GetActiveLabelSet()->SetActiveLabel(m_LabelListModel->item(row, 1)->text().toInt());
 }
 
 void ActiveLearning::OnEraseToolButtonClicked()
 {
     m_Controls.m_EraseToolButton->setChecked(true);
     m_Interactor->SetPaintingPixelValue(0);
     m_AnnotationImage->GetActiveLabelSet()->SetActiveLabel(0);
 }
 
 void ActiveLearning::OnActivateGuidancePushButtonToggled(bool toggled)
 {
 
 }
 
 void ActiveLearning::OnSaveSegmentationPushButtonClicked()
 {
 
 }
 
 void ActiveLearning::OnSavePredictionsPushButtonClicked()
 {
 
 }
 
 void ActiveLearning::OnExportSegmentationPushButtonClicked()
 {
 
 }
 
 void ActiveLearning::OnExportPredictionsPushButtonClicked()
 {
 
 }
 
 void ActiveLearning::OnColorIconDoubleClicked(const QModelIndex& index)
 {
     // Check if click is really from color icon
     if (index.column() != 0)
     {
         return;
     }
     else
     {
         // Color change dialog
         QColor setColor = QColorDialog::getColor(m_LabelListModel->itemFromIndex(index)->background().color(), m_Parent, "Select Label Color");
         if (setColor.isValid())
         {
             m_LabelListModel->itemFromIndex(index)->setBackground(setColor);
             QPixmap colorPixmap(20, 20);
             colorPixmap.fill(setColor);
             m_LabelListModel->itemFromIndex(index)->setIcon(QIcon(colorPixmap));
 
             // Set color on label
             m_AnnotationImage->GetActiveLabelSet()->GetLabel(m_LabelListModel->item(index.row(), 1)->text().toInt())->SetColor(QColorToMitkColor(setColor));
             m_AnnotationImage->GetActiveLabelSet()->UpdateLookupTable(m_LabelListModel->item(index.row(), 1)->text().toInt());
             PrintAllLabels(m_AnnotationImage);
 
             // If this is the label with value 1 we have to change the data node color
             if (m_LabelListModel->item(index.row(), 1)->text().toInt() == 1)
             {
                 m_AnnotationNode->SetColor(QColorToMitkColor(setColor));
             }
         }
     }
 }
 
 void ActiveLearning::OnLabelListSelectionChanged(const QItemSelection& selected, const QItemSelection& /*deselected*/)
 {
     if (selected.empty()) return;
     // This assumes that only one item can be selected (single selection table view)
     try
     {
         int labelValue = m_LabelListModel->item(selected.indexes()[0].row(), 1)->text().toInt();
         m_Interactor->SetPaintingPixelValue(labelValue);
         m_AnnotationImage->GetActiveLabelSet()->SetActiveLabel(labelValue);
     }
     catch (...)
     {
         m_Interactor->SetPaintingPixelValue(0);
         m_AnnotationImage->GetActiveLabelSet()->SetActiveLabel(0);
     }
 }
 
 void ActiveLearning::OnLabelNameChanged(const QModelIndex& topLeft, const QModelIndex& /*bottomRight*/)
 {
     auto item = m_LabelListModel->itemFromIndex(topLeft);
     if (item->column() != 2) return;
     m_AnnotationImage->GetActiveLabelSet()->GetLabel(m_LabelListModel->item(item->row(), 1)->text().toInt())->SetName(item->text().toStdString());
 }
 
 void ActiveLearning::OnInitializationFinished()
 {
     // Check if all futures are finished
     for (auto watcher : m_FeatureCalculationWatchers)
     {
         if (watcher->isFinished() == false) {return;}
     }
 
     // Empty feature vector
     m_FeatureImageVector.clear();
 
     // Insert features into feature vector and data storage
     for (unsigned int i=0; i<m_FeatureCalculationWatchers.size(); i++)
     {
         auto result = m_FeatureCalculationWatchers[i]->result();
         for (unsigned int j=0; j<result.size(); j++)
         {
             m_FeatureImageVector.push_back(result[j].first);
             auto node = mitk::DataNode::New();
             node->SetData(result[j].first);
             node->SetName(result[j].second);
             node->SetBoolProperty("helper object", true);
             node->SetVisibility(false);
             this->GetDataStorage()->Add(node, m_Nodes[i]);
         }
     }
 
     // Show controls
     m_Controls.m_LabelControlsFrame->setVisible(true);
     m_Controls.m_InitializePushButton->setHidden(true);
     MITK_INFO << "Features: " << m_FeatureImageVector.size();
 
     // Delete watchers
     for (auto watcher : m_FeatureCalculationWatchers)
     {
         delete watcher;
     }
     m_FeatureCalculationWatchers.clear();
 }
 
 /* ==================================================================
  * PROTECTED
  * =============================================================== */
 
 
 void ActiveLearning::OnSelectionChanged(berry::IWorkbenchPart::Pointer /*source*/,
                                         const QList<mitk::DataNode::Pointer>& nodes)
 {
     if (!SelectionAllImages(nodes))
     {
         SetInitializeReady(false);
         return;
     }
 
     if (nodes.length() >= 2)
     {
         // First selection is the reference (could be any other)
         mitk::Image::Pointer referenceImage = dynamic_cast<mitk::Image*>(nodes[0]->GetData());
         mitk::BaseGeometry* referenceGeometry = referenceImage->GetTimeGeometry()->GetGeometryForTimeStep(0); // Adjust for multiple timesteps
 
         for (int i=1; i<nodes.length(); ++i)
         {
             mitk::Image::Pointer currentImage = dynamic_cast<mitk::Image*>(nodes[i]->GetData());
             mitk::BaseGeometry* currentGeometry = currentImage->GetTimeGeometry()->GetGeometryForTimeStep(0); // Adjust for multiple timesteps
 
             if (!mitk::Equal(*currentGeometry, *referenceGeometry, mitk::eps, true))
             {
                 SetInitializeReady(false);
                 return;
             }
         }
     }
 
     // All nodes have the same geometry, allow init
     SetInitializeReady(true);
 }
 
 void ActiveLearning::SetFocus()
 {
 }
 
 
 /* ==================================================================
  * PRIVATE
  * =============================================================== */
 
 
 void ActiveLearning::SetInitializeReady(bool ready)
 {
     if (ready)
     {
         // get selection, check again just to be sure
         auto nodes = this->GetDataManagerSelection();
         if (!SelectionAllImages(nodes)) return;
 
         m_Controls.m_InitializePushButton->setEnabled(true);
 
         if (!m_Active)
         {
             QString nameList = QString::fromStdString(nodes[0]->GetName());
             if (nodes.length() >= 2)
             {
                 for (int i=1; i<nodes.length(); ++i)
                 {
                     nameList += QString("<br />");
                     nameList += QString::fromStdString(nodes[i]->GetName());
                 }
             }
             m_Controls.m_InitializeLabel->setText(nameList);
         }
     }
     else
     {
         m_Controls.m_InitializePushButton->setDisabled(true);
         if (!m_Active)
         {
             m_Controls.m_InitializeLabel->setText("<font color='red'>Selected images must have matching geometries</font>");
 
         }
     }
 }