diff --git a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp index e7f7f64ccb..bfa5041c2f 100644 --- a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp +++ b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp @@ -1,552 +1,552 @@ /*============================================================================ 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 "mitkImageStatisticsCalculator.h" #include #include #include #include #include #include #include #include #include #include #include #include namespace mitk { void ImageStatisticsCalculator::SetInputImage(const mitk::Image *image) { if (image != m_Image) { m_Image = image; this->Modified(); } } void ImageStatisticsCalculator::SetMask(mitk::MaskGenerator *mask) { if (mask != m_MaskGenerator) { m_MaskGenerator = mask; this->Modified(); } } void ImageStatisticsCalculator::SetSecondaryMask(mitk::MaskGenerator *mask) { if (mask != m_SecondaryMaskGenerator) { m_SecondaryMaskGenerator = mask; this->Modified(); } } void ImageStatisticsCalculator::SetNBinsForHistogramStatistics(unsigned int nBins) { if (nBins != m_nBinsForHistogramStatistics) { m_nBinsForHistogramStatistics = nBins; this->Modified(); this->m_UseBinSizeOverNBins = false; } if (m_UseBinSizeOverNBins) { this->Modified(); this->m_UseBinSizeOverNBins = false; } } unsigned int ImageStatisticsCalculator::GetNBinsForHistogramStatistics() const { return m_nBinsForHistogramStatistics; } void ImageStatisticsCalculator::SetBinSizeForHistogramStatistics(double binSize) { if (binSize != m_binSizeForHistogramStatistics) { m_binSizeForHistogramStatistics = binSize; this->Modified(); this->m_UseBinSizeOverNBins = true; } if (!m_UseBinSizeOverNBins) { this->Modified(); this->m_UseBinSizeOverNBins = true; } } double ImageStatisticsCalculator::GetBinSizeForHistogramStatistics() const { return m_binSizeForHistogramStatistics; } mitk::ImageStatisticsContainer* ImageStatisticsCalculator::GetStatistics(LabelIndex label) { if (m_Image.IsNull()) { mitkThrow() << "no image"; } if (!m_Image->IsInitialized()) { mitkThrow() << "Image not initialized!"; } if (IsUpdateRequired(label)) { auto timeGeometry = m_Image->GetTimeGeometry(); // always compute statistics on all timesteps for (unsigned int timeStep = 0; timeStep < m_Image->GetTimeSteps(); timeStep++) { if (m_MaskGenerator.IsNotNull()) { m_MaskGenerator->SetTimeStep(timeStep); //See T25625: otherwise, the mask is not computed again after setting a different time step m_MaskGenerator->Modified(); m_InternalMask = m_MaskGenerator->GetMask(); if (m_MaskGenerator->GetReferenceImage().IsNotNull()) { m_InternalImageForStatistics = m_MaskGenerator->GetReferenceImage(); } else { m_InternalImageForStatistics = m_Image; } } else { m_InternalImageForStatistics = m_Image; } if (m_SecondaryMaskGenerator.IsNotNull()) { m_SecondaryMaskGenerator->SetTimeStep(timeStep); m_SecondaryMask = m_SecondaryMaskGenerator->GetMask(); } ImageTimeSelector::Pointer imgTimeSel = ImageTimeSelector::New(); imgTimeSel->SetInput(m_InternalImageForStatistics); imgTimeSel->SetTimeNr(timeStep); imgTimeSel->UpdateLargestPossibleRegion(); imgTimeSel->Update(); m_ImageTimeSlice = imgTimeSel->GetOutput(); // Calculate statistics with/without mask if (m_MaskGenerator.IsNull() && m_SecondaryMaskGenerator.IsNull()) { // 1) calculate statistics unmasked: AccessByItk_2(m_ImageTimeSlice, InternalCalculateStatisticsUnmasked, timeGeometry, timeStep) } else { // 2) calculate statistics masked AccessByItk_2(m_ImageTimeSlice, InternalCalculateStatisticsMasked, timeGeometry, timeStep) } } } auto it = m_StatisticContainers.find(label); if (it != m_StatisticContainers.end()) { return (it->second).GetPointer(); } else { mitkThrow() << "unknown label"; return nullptr; } } template void ImageStatisticsCalculator::InternalCalculateStatisticsUnmasked( typename itk::Image *image, const TimeGeometry *timeGeometry, TimeStepType timeStep) { typedef typename itk::Image ImageType; typedef typename itk::ExtendedStatisticsImageFilter ImageStatisticsFilterType; typedef typename itk::MinMaxImageFilterWithIndex MinMaxFilterType; // reset statistics container if exists ImageStatisticsContainer::Pointer statisticContainerForImage; LabelIndex labelNoMask = 1; auto it = m_StatisticContainers.find(labelNoMask); if (it != m_StatisticContainers.end()) { statisticContainerForImage = it->second; } else { statisticContainerForImage = ImageStatisticsContainer::New(); statisticContainerForImage->SetTimeGeometry(const_cast(timeGeometry)); m_StatisticContainers.emplace(labelNoMask, statisticContainerForImage); } auto statObj = ImageStatisticsContainer::ImageStatisticsObject(); typename ImageStatisticsFilterType::Pointer statisticsFilter = ImageStatisticsFilterType::New(); statisticsFilter->SetInput(image); statisticsFilter->SetCoordinateTolerance(0.001); statisticsFilter->SetDirectionTolerance(0.001); // TODO: this is single threaded. Implement our own image filter that does this multi threaded // typename itk::MinimumMaximumImageCalculator::Pointer imgMinMaxFilter = // itk::MinimumMaximumImageCalculator::New(); imgMinMaxFilter->SetImage(image); // imgMinMaxFilter->Compute(); vnl_vector minIndex, maxIndex; typename MinMaxFilterType::Pointer minMaxFilter = MinMaxFilterType::New(); minMaxFilter->SetInput(image); minMaxFilter->UpdateLargestPossibleRegion(); typename ImageType::PixelType minval = minMaxFilter->GetMin(); typename ImageType::PixelType maxval = minMaxFilter->GetMax(); typename ImageType::IndexType tmpMinIndex = minMaxFilter->GetMinIndex(); typename ImageType::IndexType tmpMaxIndex = minMaxFilter->GetMaxIndex(); // typename ImageType::IndexType tmpMinIndex = imgMinMaxFilter->GetIndexOfMinimum(); // typename ImageType::IndexType tmpMaxIndex = imgMinMaxFilter->GetIndexOfMaximum(); minIndex.set_size(tmpMaxIndex.GetIndexDimension()); maxIndex.set_size(tmpMaxIndex.GetIndexDimension()); for (unsigned int i = 0; i < tmpMaxIndex.GetIndexDimension(); i++) { minIndex[i] = tmpMinIndex[i]; maxIndex[i] = tmpMaxIndex[i]; } statObj.AddStatistic(mitk::ImageStatisticsConstants::MINIMUMPOSITION(), minIndex); statObj.AddStatistic(mitk::ImageStatisticsConstants::MAXIMUMPOSITION(), maxIndex); // convert m_binSize in m_nBins if necessary unsigned int nBinsForHistogram; if (m_UseBinSizeOverNBins) { nBinsForHistogram = std::max(static_cast(std::ceil(maxval - minval)) / m_binSizeForHistogramStatistics, 10.); // do not allow less than 10 bins } else { nBinsForHistogram = m_nBinsForHistogramStatistics; } statisticsFilter->SetHistogramParameters(nBinsForHistogram, minval, maxval); try { statisticsFilter->Update(); } catch (const itk::ExceptionObject &e) { mitkThrow() << "Image statistics calculation failed due to following ITK Exception: \n " << e.what(); } auto voxelVolume = GetVoxelVolume(image); auto numberOfPixels = image->GetLargestPossibleRegion().GetNumberOfPixels(); auto volume = static_cast(numberOfPixels) * voxelVolume; auto variance = statisticsFilter->GetSigma() * statisticsFilter->GetSigma(); auto rms = std::sqrt(std::pow(statisticsFilter->GetMean(), 2.) + statisticsFilter->GetVariance()); // variance = sigma^2 statObj.AddStatistic(mitk::ImageStatisticsConstants::NUMBEROFVOXELS(), static_cast(numberOfPixels)); statObj.AddStatistic(mitk::ImageStatisticsConstants::VOLUME(), volume); statObj.AddStatistic(mitk::ImageStatisticsConstants::MEAN(), statisticsFilter->GetMean()); statObj.AddStatistic(mitk::ImageStatisticsConstants::MINIMUM(), static_cast(statisticsFilter->GetMinimum())); statObj.AddStatistic(mitk::ImageStatisticsConstants::MAXIMUM(), static_cast(statisticsFilter->GetMaximum())); statObj.AddStatistic(mitk::ImageStatisticsConstants::STANDARDDEVIATION(), statisticsFilter->GetSigma()); statObj.AddStatistic(mitk::ImageStatisticsConstants::VARIANCE(), variance); statObj.AddStatistic(mitk::ImageStatisticsConstants::SKEWNESS(), statisticsFilter->GetSkewness()); statObj.AddStatistic(mitk::ImageStatisticsConstants::KURTOSIS(), statisticsFilter->GetKurtosis()); statObj.AddStatistic(mitk::ImageStatisticsConstants::RMS(), rms); statObj.AddStatistic(mitk::ImageStatisticsConstants::MPP(), statisticsFilter->GetMPP()); statObj.AddStatistic(mitk::ImageStatisticsConstants::ENTROPY(), statisticsFilter->GetEntropy()); statObj.AddStatistic(mitk::ImageStatisticsConstants::MEDIAN(), statisticsFilter->GetMedian()); statObj.AddStatistic(mitk::ImageStatisticsConstants::UNIFORMITY(), statisticsFilter->GetUniformity()); statObj.AddStatistic(mitk::ImageStatisticsConstants::UPP(), statisticsFilter->GetUPP()); statObj.m_Histogram = statisticsFilter->GetHistogram().GetPointer(); statisticContainerForImage->SetStatisticsForTimeStep(timeStep, statObj); } template double ImageStatisticsCalculator::GetVoxelVolume(typename itk::Image *image) const { auto spacing = image->GetSpacing(); double voxelVolume = 1.; for (unsigned int i = 0; i < image->GetImageDimension(); i++) { voxelVolume *= spacing[i]; } return voxelVolume; } template void ImageStatisticsCalculator::InternalCalculateStatisticsMasked(typename itk::Image *image, const TimeGeometry *timeGeometry, unsigned int timeStep) { typedef itk::Image ImageType; typedef itk::Image MaskType; typedef typename MaskType::PixelType LabelPixelType; typedef itk::ExtendedLabelStatisticsImageFilter ImageStatisticsFilterType; typedef MaskUtilities MaskUtilType; typedef typename itk::MinMaxLabelImageFilterWithIndex MinMaxLabelFilterType; typedef typename ImageType::PixelType InputImgPixelType; // workaround: if m_SecondaryMaskGenerator ist not null but m_MaskGenerator is! (this is the case if we request a // 'ignore zuero valued pixels' mask in the gui but do not define a primary mask) bool swapMasks = false; if (m_SecondaryMask.IsNotNull() && m_InternalMask.IsNull()) { m_InternalMask = m_SecondaryMask; m_SecondaryMask = nullptr; swapMasks = true; } // maskImage has to have the same dimension as image typename MaskType::Pointer maskImage = MaskType::New(); try { // try to access the pixel values directly (no copying or casting). Only works if mask pixels are of pixelType // unsigned short maskImage = ImageToItkImage(m_InternalMask); } catch (const itk::ExceptionObject &) { // if the pixel type of the mask is not short, then we have to make a copy of m_InternalMask (and cast the values) CastToItkImage(m_InternalMask, maskImage); } // if we have a secondary mask (say a ignoreZeroPixelMask) we need to combine the masks (corresponds to AND) if (m_SecondaryMask.IsNotNull()) { // dirty workaround for a bug when pf mask + any other mask is used in conjunction. We need a proper fix for this // (Fabian Isensee is responsible and probably working on it!) if (m_InternalMask->GetDimension() == 2 && (m_SecondaryMask->GetDimension() == 3 || m_SecondaryMask->GetDimension() == 4)) { mitk::Image::ConstPointer old_img = m_SecondaryMaskGenerator->GetReferenceImage(); m_SecondaryMaskGenerator->SetInputImage(m_MaskGenerator->GetReferenceImage()); m_SecondaryMask = m_SecondaryMaskGenerator->GetMask(); m_SecondaryMaskGenerator->SetInputImage(old_img); } typename MaskType::Pointer secondaryMaskImage = MaskType::New(); secondaryMaskImage = ImageToItkImage(m_SecondaryMask); // secondary mask should be a ignore zero value pixel mask derived from image. it has to be cropped to the mask // region (which may be planar or simply smaller) typename MaskUtilities::Pointer secondaryMaskMaskUtil = MaskUtilities::New(); secondaryMaskMaskUtil->SetImage(secondaryMaskImage.GetPointer()); secondaryMaskMaskUtil->SetMask(maskImage.GetPointer()); typename MaskType::Pointer adaptedSecondaryMaskImage = secondaryMaskMaskUtil->ExtractMaskImageRegion(); typename itk::MaskImageFilter2::Pointer maskFilter = itk::MaskImageFilter2::New(); maskFilter->SetInput1(maskImage); maskFilter->SetInput2(adaptedSecondaryMaskImage); maskFilter->SetMaskingValue( 1); // all pixels of maskImage where secondaryMaskImage==1 will be kept, all the others are set to 0 maskFilter->UpdateLargestPossibleRegion(); maskImage = maskFilter->GetOutput(); } typename MaskUtilType::Pointer maskUtil = MaskUtilType::New(); maskUtil->SetImage(image); maskUtil->SetMask(maskImage.GetPointer()); // if mask is smaller than image, extract the image region where the mask is typename ImageType::Pointer adaptedImage = ImageType::New(); adaptedImage = maskUtil->ExtractMaskImageRegion(); // this also checks mask sanity // find min, max, minindex and maxindex typename MinMaxLabelFilterType::Pointer minMaxFilter = MinMaxLabelFilterType::New(); minMaxFilter->SetInput(adaptedImage); minMaxFilter->SetLabelInput(maskImage); minMaxFilter->UpdateLargestPossibleRegion(); // set histogram parameters for each label individually (min/max may be different for each label) typedef typename std::map MapType; typedef typename std::pair PairType; std::vector relevantLabels = minMaxFilter->GetRelevantLabels(); MapType minVals; MapType maxVals; std::map nBins; for (LabelPixelType label : relevantLabels) { minVals.insert(PairType(label, minMaxFilter->GetMin(label))); maxVals.insert(PairType(label, minMaxFilter->GetMax(label))); unsigned int nBinsForHistogram; if (m_UseBinSizeOverNBins) { nBinsForHistogram = std::max(static_cast(std::ceil(minMaxFilter->GetMax(label) - minMaxFilter->GetMin(label))) / m_binSizeForHistogramStatistics, 10.); // do not allow less than 10 bins } else { nBinsForHistogram = m_nBinsForHistogramStatistics; } nBins.insert(typename std::pair(label, nBinsForHistogram)); } typename ImageStatisticsFilterType::Pointer imageStatisticsFilter = ImageStatisticsFilterType::New(); imageStatisticsFilter->SetDirectionTolerance(0.001); imageStatisticsFilter->SetCoordinateTolerance(0.001); imageStatisticsFilter->SetInput(adaptedImage); imageStatisticsFilter->SetLabelInput(maskImage); imageStatisticsFilter->SetHistogramParametersForLabels(nBins, minVals, maxVals); imageStatisticsFilter->Update(); std::list labels = imageStatisticsFilter->GetRelevantLabels(); auto it = labels.begin(); while (it != labels.end()) { ImageStatisticsContainer::Pointer statisticContainerForLabelImage; auto labelIt = m_StatisticContainers.find(*it); // reset if statisticContainer already exist if (labelIt != m_StatisticContainers.end()) { statisticContainerForLabelImage = labelIt->second; } // create new statisticContainer else { statisticContainerForLabelImage = ImageStatisticsContainer::New(); statisticContainerForLabelImage->SetTimeGeometry(const_cast(timeGeometry)); // link label (*it) to statisticContainer m_StatisticContainers.emplace(*it, statisticContainerForLabelImage); } ImageStatisticsContainer::ImageStatisticsObject statObj; // find min, max, minindex and maxindex // make sure to only look in the masked region, use a masker for this vnl_vector minIndex, maxIndex; mitk::Point3D worldCoordinateMin; mitk::Point3D worldCoordinateMax; mitk::Point3D indexCoordinateMin; mitk::Point3D indexCoordinateMax; m_InternalImageForStatistics->GetGeometry()->IndexToWorld(minMaxFilter->GetMinIndex(*it), worldCoordinateMin); m_InternalImageForStatistics->GetGeometry()->IndexToWorld(minMaxFilter->GetMaxIndex(*it), worldCoordinateMax); m_Image->GetGeometry()->WorldToIndex(worldCoordinateMin, indexCoordinateMin); m_Image->GetGeometry()->WorldToIndex(worldCoordinateMax, indexCoordinateMax); minIndex.set_size(3); maxIndex.set_size(3); // for (unsigned int i=0; i < tmpMaxIndex.GetIndexDimension(); i++) for (unsigned int i = 0; i < 3; i++) { minIndex[i] = indexCoordinateMin[i]; maxIndex[i] = indexCoordinateMax[i]; } statObj.AddStatistic(mitk::ImageStatisticsConstants::MINIMUMPOSITION(), minIndex); statObj.AddStatistic(mitk::ImageStatisticsConstants::MAXIMUMPOSITION(), maxIndex); assert(std::abs(minMaxFilter->GetMax(*it) - imageStatisticsFilter->GetMaximum(*it)) < mitk::eps); assert(std::abs(minMaxFilter->GetMin(*it) - imageStatisticsFilter->GetMinimum(*it)) < mitk::eps); auto voxelVolume = GetVoxelVolume(image); auto numberOfVoxels = - static_cast(imageStatisticsFilter->GetSum(*it) / (double)imageStatisticsFilter->GetMean(*it)); + static_cast(imageStatisticsFilter->GetCount(*it)); auto volume = static_cast(numberOfVoxels) * voxelVolume; auto rms = std::sqrt(std::pow(imageStatisticsFilter->GetMean(*it), 2.) + imageStatisticsFilter->GetVariance(*it)); // variance = sigma^2 auto variance = imageStatisticsFilter->GetSigma(*it) * imageStatisticsFilter->GetSigma(*it); statObj.AddStatistic(mitk::ImageStatisticsConstants::NUMBEROFVOXELS(), numberOfVoxels); statObj.AddStatistic(mitk::ImageStatisticsConstants::VOLUME(), volume); statObj.AddStatistic(mitk::ImageStatisticsConstants::MEAN(), imageStatisticsFilter->GetMean(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::MINIMUM(), imageStatisticsFilter->GetMinimum(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::MAXIMUM(), imageStatisticsFilter->GetMaximum(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::STANDARDDEVIATION(), imageStatisticsFilter->GetSigma(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::VARIANCE(), variance); statObj.AddStatistic(mitk::ImageStatisticsConstants::SKEWNESS(), imageStatisticsFilter->GetSkewness(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::KURTOSIS(), imageStatisticsFilter->GetKurtosis(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::RMS(), rms); statObj.AddStatistic(mitk::ImageStatisticsConstants::MPP(), imageStatisticsFilter->GetMPP(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::ENTROPY(), imageStatisticsFilter->GetEntropy(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::MEDIAN(), imageStatisticsFilter->GetMedian(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::UNIFORMITY(), imageStatisticsFilter->GetUniformity(*it)); statObj.AddStatistic(mitk::ImageStatisticsConstants::UPP(), imageStatisticsFilter->GetUPP(*it)); statObj.m_Histogram = imageStatisticsFilter->GetHistogram(*it).GetPointer(); statisticContainerForLabelImage->SetStatisticsForTimeStep(timeStep, statObj); ++it; } // swap maskGenerators back if (swapMasks) { m_SecondaryMask = m_InternalMask; m_InternalMask = nullptr; } } bool ImageStatisticsCalculator::IsUpdateRequired(LabelIndex label) const { unsigned long thisClassTimeStamp = this->GetMTime(); unsigned long inputImageTimeStamp = m_Image->GetMTime(); auto it = m_StatisticContainers.find(label); if (it == m_StatisticContainers.end()) { return true; } unsigned long statisticsTimeStamp = it->second->GetMTime(); if (thisClassTimeStamp > statisticsTimeStamp) // inputs have changed { return true; } if (inputImageTimeStamp > statisticsTimeStamp) // image has changed { return true; } if (m_MaskGenerator.IsNotNull()) { unsigned long maskGeneratorTimeStamp = m_MaskGenerator->GetMTime(); if (maskGeneratorTimeStamp > statisticsTimeStamp) // there is a mask generator and it has changed { return true; } } if (m_SecondaryMaskGenerator.IsNotNull()) { unsigned long maskGeneratorTimeStamp = m_SecondaryMaskGenerator->GetMTime(); if (maskGeneratorTimeStamp > statisticsTimeStamp) // there is a secondary mask generator and it has changed { return true; } } return false; } } // namespace mitk diff --git a/Modules/ImageStatistics/mitkImageStatisticsContainer.cpp b/Modules/ImageStatistics/mitkImageStatisticsContainer.cpp index 6b8851bdd4..0f63304ab9 100644 --- a/Modules/ImageStatistics/mitkImageStatisticsContainer.cpp +++ b/Modules/ImageStatistics/mitkImageStatisticsContainer.cpp @@ -1,240 +1,248 @@ /*============================================================================ 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 #include namespace mitk { ImageStatisticsContainer::ImageStatisticsContainer() { this->Reset(); } // The order is derived from the old (<2018) image statistics plugin. const ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector ImageStatisticsContainer::ImageStatisticsObject::m_DefaultNames = {ImageStatisticsConstants::MEAN(), ImageStatisticsConstants::MEDIAN(), ImageStatisticsConstants::STANDARDDEVIATION(), ImageStatisticsConstants::RMS(), ImageStatisticsConstants::MAXIMUM(), ImageStatisticsConstants::MAXIMUMPOSITION(), ImageStatisticsConstants::MINIMUM(), ImageStatisticsConstants::MINIMUMPOSITION(), ImageStatisticsConstants::NUMBEROFVOXELS(), ImageStatisticsConstants::VOLUME(), ImageStatisticsConstants::SKEWNESS(), ImageStatisticsConstants::KURTOSIS(), ImageStatisticsConstants::UNIFORMITY(), ImageStatisticsConstants::ENTROPY(), ImageStatisticsConstants::MPP(), ImageStatisticsConstants::UPP()}; ImageStatisticsContainer::ImageStatisticsObject::ImageStatisticsObject() { Reset(); } void ImageStatisticsContainer::ImageStatisticsObject::AddStatistic(const std::string &key, StatisticsVariantType value) { m_Statistics.emplace(key, value); if (std::find(m_DefaultNames.cbegin(), m_DefaultNames.cend(), key) == m_DefaultNames.cend()) { if (std::find(m_CustomNames.cbegin(), m_CustomNames.cend(), key) == m_CustomNames.cend()) { m_CustomNames.emplace_back(key); } } } const ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector & ImageStatisticsContainer::ImageStatisticsObject::GetDefaultStatisticNames() { return m_DefaultNames; } const ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector & ImageStatisticsContainer::ImageStatisticsObject::GetCustomStatisticNames() const { return m_CustomNames; } ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector ImageStatisticsContainer::ImageStatisticsObject::GetAllStatisticNames() const { StatisticNameVector names = GetDefaultStatisticNames(); names.insert(names.cend(), m_CustomNames.cbegin(), m_CustomNames.cend()); return names; } ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector ImageStatisticsContainer::ImageStatisticsObject::GetExistingStatisticNames() const { StatisticNameVector names; std::transform(m_Statistics.begin(), m_Statistics.end(), std::back_inserter(names), [](const auto &pair) { return pair.first; }); return names; } bool ImageStatisticsContainer::ImageStatisticsObject::HasStatistic(const std::string &name) const { return m_Statistics.find(name) != m_Statistics.cend(); } ImageStatisticsContainer::StatisticsVariantType ImageStatisticsContainer::ImageStatisticsObject::GetValueNonConverted( const std::string &name) const { if (HasStatistic(name)) { return m_Statistics.find(name)->second; } else { mitkThrow() << "invalid statistic key, could not find"; } } void ImageStatisticsContainer::ImageStatisticsObject::Reset() { m_Statistics.clear(); m_CustomNames.clear(); } bool ImageStatisticsContainer::TimeStepExists(TimeStepType timeStep) const { return m_TimeStepMap.find(timeStep) != m_TimeStepMap.end(); } const ImageStatisticsContainer::HistogramType* ImageStatisticsContainer::GetHistogramForTimeStep(TimeStepType timeStep) const { return this->GetStatisticsForTimeStep(timeStep).m_Histogram; } const ImageStatisticsContainer::ImageStatisticsObject &ImageStatisticsContainer::GetStatisticsForTimeStep( TimeStepType timeStep) const { auto it = m_TimeStepMap.find(timeStep); if (it != m_TimeStepMap.end()) { return it->second; } mitkThrow() << "StatisticsObject for timeStep " << timeStep << " not found!"; } void ImageStatisticsContainer::SetStatisticsForTimeStep(TimeStepType timeStep, ImageStatisticsObject statistics) { if (timeStep < this->GetTimeSteps()) { m_TimeStepMap.emplace(timeStep, statistics); this->Modified(); } else { mitkThrow() << "Given timeStep " << timeStep << " out of timeStep geometry bounds. TimeSteps in geometry: " << this->GetTimeSteps(); } } void ImageStatisticsContainer::PrintSelf(std::ostream &os, itk::Indent indent) const { Superclass::PrintSelf(os, indent); for (unsigned int i = 0; i < this->GetTimeSteps(); i++) { - auto statisticsValues = GetStatisticsForTimeStep(i); os << std::endl << indent << "Statistics instance for timeStep " << i << ":"; - auto statisticKeys = statisticsValues.GetExistingStatisticNames(); - os << std::endl << indent << "Number of entries: " << statisticKeys.size(); - for (const auto &aKey : statisticKeys) + if (this->TimeStepExists(i)) { - os << std::endl << indent.GetNextIndent() << aKey << ": " << statisticsValues.GetValueNonConverted(aKey); + auto statisticsValues = GetStatisticsForTimeStep(i); + + auto statisticKeys = statisticsValues.GetExistingStatisticNames(); + os << std::endl << indent << "Number of entries: " << statisticKeys.size(); + for (const auto& aKey : statisticKeys) + { + os << std::endl << indent.GetNextIndent() << aKey << ": " << statisticsValues.GetValueNonConverted(aKey); + } + } + else + { + os << std::endl << indent << "N/A"; } } } unsigned int ImageStatisticsContainer::GetNumberOfTimeSteps() const { return this->GetTimeSteps(); } void ImageStatisticsContainer::Reset() { for (auto iter = m_TimeStepMap.begin(); iter != m_TimeStepMap.end(); iter++) { iter->second.Reset(); } } itk::LightObject::Pointer ImageStatisticsContainer::InternalClone() const { itk::LightObject::Pointer ioPtr = Superclass::InternalClone(); Self::Pointer rval = dynamic_cast(ioPtr.GetPointer()); if (rval.IsNull()) { itkExceptionMacro(<< "downcast to type " << "StatisticsContainer" << " failed."); } rval->SetTimeStepMap(m_TimeStepMap); rval->SetTimeGeometry(this->GetTimeGeometry()->Clone()); return ioPtr; } void ImageStatisticsContainer::SetTimeStepMap(TimeStepMapType map) { m_TimeStepMap = map; } ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector GetAllStatisticNames( const ImageStatisticsContainer *container) { ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector names = ImageStatisticsContainer::ImageStatisticsObject::GetDefaultStatisticNames(); if (container) { std::set customKeys; for (unsigned int i = 0; i < container->GetTimeSteps(); i++) { auto statisticKeys = container->GetStatisticsForTimeStep(i).GetCustomStatisticNames(); customKeys.insert(statisticKeys.cbegin(), statisticKeys.cend()); } names.insert(names.cend(), customKeys.cbegin(), customKeys.cend()); } return names; } ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector GetAllStatisticNames( std::vector containers) { ImageStatisticsContainer::ImageStatisticsObject::StatisticNameVector names = ImageStatisticsContainer::ImageStatisticsObject::GetDefaultStatisticNames(); std::set customKeys; for (const auto &container : containers) { for (unsigned int i = 0; i < container->GetTimeSteps(); i++) { if(container->TimeStepExists(i)) { auto statisticKeys = container->GetStatisticsForTimeStep(i).GetCustomStatisticNames(); customKeys.insert(statisticKeys.cbegin(), statisticKeys.cend()); } } } names.insert(names.end(), customKeys.begin(), customKeys.end()); return names; }; } // namespace mitk diff --git a/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp b/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp index 60f918782e..8f8fd8b572 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp @@ -1,473 +1,476 @@ /*============================================================================ 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 "QmitkImageStatisticsView.h" #include // berry includes #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include "mitkPlanarFigureMaskGenerator.h" #include "QmitkImageStatisticsDataGenerator.h" #include "mitkImageStatisticsContainerManager.h" #include const std::string QmitkImageStatisticsView::VIEW_ID = "org.mitk.views.imagestatistics"; QmitkImageStatisticsView::~QmitkImageStatisticsView() { } void QmitkImageStatisticsView::CreateQtPartControl(QWidget *parent) { m_Controls.setupUi(parent); m_Controls.widget_intensityProfile->SetTheme(GetColorTheme()); m_Controls.groupBox_histogram->setVisible(true); m_Controls.groupBox_intensityProfile->setVisible(false); m_Controls.label_currentlyComputingStatistics->setVisible(false); m_Controls.sliderWidget_histogram->setPrefix("Time: "); m_Controls.sliderWidget_histogram->setDecimals(0); m_Controls.sliderWidget_histogram->setVisible(false); m_Controls.sliderWidget_intensityProfile->setPrefix("Time: "); m_Controls.sliderWidget_intensityProfile->setDecimals(0); m_Controls.sliderWidget_intensityProfile->setVisible(false); ResetGUI(); m_DataGenerator = new QmitkImageStatisticsDataGenerator(parent); m_DataGenerator->SetDataStorage(this->GetDataStorage()); m_DataGenerator->SetAutoUpdate(true); m_Controls.widget_statistics->SetDataStorage(this->GetDataStorage()); m_Controls.imageNodesSelector->SetDataStorage(this->GetDataStorage()); m_Controls.imageNodesSelector->SetNodePredicate(mitk::GetImageStatisticsImagePredicate()); m_Controls.imageNodesSelector->SetSelectionCheckFunction(this->CheckForSameGeometry()); m_Controls.imageNodesSelector->SetSelectionIsOptional(false); m_Controls.imageNodesSelector->SetInvalidInfo(QStringLiteral("Please select images for statistics")); m_Controls.imageNodesSelector->SetPopUpTitel(QStringLiteral("Select input images")); m_Controls.roiNodesSelector->SetPopUpHint(QStringLiteral("You may select multiple images for the statistics computation. But all selected images must have the same geometry.")); m_Controls.roiNodesSelector->SetDataStorage(this->GetDataStorage()); m_Controls.roiNodesSelector->SetNodePredicate(this->GenerateROIPredicate()); m_Controls.roiNodesSelector->SetSelectionIsOptional(true); m_Controls.roiNodesSelector->SetEmptyInfo(QStringLiteral("Please select ROIs")); m_Controls.roiNodesSelector->SetPopUpTitel(QStringLiteral("Select ROIs for statistics computation")); m_Controls.roiNodesSelector->SetPopUpHint(QStringLiteral("You may select ROIs (e.g. planar figures, segmentations) that should be used for the statistics computation. The statistics will only computed for the image parts defined by the ROIs.")); CreateConnections(); this->m_TimePointChangeListener.RenderWindowPartActivated(this->GetRenderWindowPart()); connect(&m_TimePointChangeListener, &QmitkSliceNavigationListener::SelectedTimePointChanged, this, & QmitkImageStatisticsView::OnSelectedTimePointChanged); } void QmitkImageStatisticsView::RenderWindowPartActivated(mitk::IRenderWindowPart* renderWindowPart) { this->m_TimePointChangeListener.RenderWindowPartActivated(renderWindowPart); } void QmitkImageStatisticsView::RenderWindowPartDeactivated(mitk::IRenderWindowPart* renderWindowPart) { this->m_TimePointChangeListener.RenderWindowPartDeactivated(renderWindowPart); } void QmitkImageStatisticsView::CreateConnections() { connect(m_Controls.checkBox_ignoreZero, &QCheckBox::stateChanged, this, &QmitkImageStatisticsView::OnCheckBoxIgnoreZeroStateChanged); connect(m_Controls.buttonSelection, &QAbstractButton::clicked, this, &QmitkImageStatisticsView::OnButtonSelectionPressed); connect(m_Controls.widget_histogram, &QmitkHistogramVisualizationWidget::RequestHistogramUpdate, this, &QmitkImageStatisticsView::OnRequestHistogramUpdate); connect(m_DataGenerator, &QmitkImageStatisticsDataGenerator::DataGenerationStarted, this, &QmitkImageStatisticsView::OnGenerationStarted); connect(m_DataGenerator, &QmitkImageStatisticsDataGenerator::GenerationFinished, this, &QmitkImageStatisticsView::OnGenerationFinished); connect(m_DataGenerator, &QmitkImageStatisticsDataGenerator::JobError, this, &QmitkImageStatisticsView::OnJobError); connect(m_Controls.imageNodesSelector, &QmitkAbstractNodeSelectionWidget::CurrentSelectionChanged, this, &QmitkImageStatisticsView::OnImageSelectionChanged); connect(m_Controls.roiNodesSelector, &QmitkAbstractNodeSelectionWidget::CurrentSelectionChanged, this, &QmitkImageStatisticsView::OnROISelectionChanged); connect(m_Controls.sliderWidget_intensityProfile, &ctkSliderWidget::valueChanged, this, &QmitkImageStatisticsView::UpdateIntensityProfile); } void QmitkImageStatisticsView::UpdateIntensityProfile() { m_Controls.groupBox_intensityProfile->setVisible(false); const auto selectedImageNodes = m_Controls.imageNodesSelector->GetSelectedNodes(); const auto selectedROINodes = m_Controls.roiNodesSelector->GetSelectedNodes(); if (selectedImageNodes.size()==1 && selectedROINodes.size()==1) { //only supported for one image and roi currently auto image = dynamic_cast(selectedImageNodes.front()->GetData()); auto maskPlanarFigure = dynamic_cast(selectedROINodes.front()->GetData()); if (maskPlanarFigure != nullptr) { if (!maskPlanarFigure->IsClosed()) { mitk::Image::Pointer inputImage; if (image->GetDimension() == 4) { m_Controls.sliderWidget_intensityProfile->setVisible(true); unsigned int maxTimestep = image->GetTimeSteps(); m_Controls.sliderWidget_intensityProfile->setMaximum(maxTimestep - 1); // Intensity profile can only be calculated on 3D, so extract if 4D mitk::ImageTimeSelector::Pointer timeSelector = mitk::ImageTimeSelector::New(); int currentTimestep = static_cast(m_Controls.sliderWidget_intensityProfile->value()); timeSelector->SetInput(image); timeSelector->SetTimeNr(currentTimestep); timeSelector->Update(); inputImage = timeSelector->GetOutput(); } else { m_Controls.sliderWidget_intensityProfile->setVisible(false); inputImage = image; } auto intensityProfile = mitk::ComputeIntensityProfile(inputImage, maskPlanarFigure); m_Controls.groupBox_intensityProfile->setVisible(true); m_Controls.widget_intensityProfile->Reset(); m_Controls.widget_intensityProfile->SetIntensityProfile(intensityProfile.GetPointer(), "Intensity Profile of " + selectedImageNodes.front()->GetName()); } } } } void QmitkImageStatisticsView::UpdateHistogramWidget() { bool visibility = false; const auto selectedImageNodes = m_Controls.imageNodesSelector->GetSelectedNodes(); const auto selectedMaskNodes = m_Controls.roiNodesSelector->GetSelectedNodes(); if (selectedImageNodes.size() == 1 && selectedMaskNodes.size()<=1) { //currently only supported for one image and roi due to histogram widget limitations. auto imageNode = selectedImageNodes.front(); const mitk::DataNode* roiNode = nullptr; const mitk::PlanarFigure* planarFigure = nullptr; if (!selectedMaskNodes.empty()) { roiNode = selectedMaskNodes.front(); planarFigure = dynamic_cast(roiNode->GetData()); } if ((planarFigure == nullptr || planarFigure->IsClosed()) && imageNode->GetData()->GetTimeGeometry()->IsValidTimePoint(m_TimePointChangeListener.GetCurrentSelectedTimePoint())) { //if a planar figure is not closed, we show the intensity profile instead of the histogram. auto statisticsNode = m_DataGenerator->GetLatestResult(imageNode, roiNode, true); if (statisticsNode.IsNotNull()) { auto statistics = dynamic_cast(statisticsNode->GetData()); if (statistics) { const auto timeStep = imageNode->GetData()->GetTimeGeometry()->TimePointToTimeStep(m_TimePointChangeListener.GetCurrentSelectedTimePoint()); - std::stringstream label; - label << imageNode->GetName(); - if (imageNode->GetData()->GetTimeSteps() > 1) + if (statistics->TimeStepExists(timeStep)) { - label << "["<< timeStep <<"]"; + std::stringstream label; + label << imageNode->GetName(); + if (imageNode->GetData()->GetTimeSteps() > 1) + { + label << "[" << timeStep << "]"; + } + + if (roiNode) + { + label << " with " << roiNode->GetName(); + } + + //Hardcoded labels are currently needed because the current histogram widget (and ChartWidget) + //do not allow correct removal or sound update/insertion of serveral charts. + //only thing that works for now is always to update/overwrite the same data label + //This is a quick fix for T28223 and T28221 + m_Controls.widget_histogram->SetHistogram(statistics->GetHistogramForTimeStep(timeStep), "histogram"); + + visibility = true; } - - if (roiNode) - { - label << " with " << roiNode->GetName(); - } - - //Hardcoded labels are currently needed because the current histogram widget (and ChartWidget) - //do not allow correct removal or sound update/insertion of serveral charts. - //only thing that works for now is always to update/overwrite the same data label - //This is a quick fix for T28223 and T28221 - m_Controls.widget_histogram->SetHistogram(statistics->GetHistogramForTimeStep(timeStep), "histogram"); - - visibility = true; } } } } if (visibility != m_Controls.groupBox_histogram->isVisible()) { m_Controls.groupBox_histogram->setVisible(visibility); } } QmitkChartWidget::ColorTheme QmitkImageStatisticsView::GetColorTheme() const { ctkPluginContext *context = berry::WorkbenchPlugin::GetDefault()->GetPluginContext(); ctkServiceReference styleManagerRef = context->getServiceReference(); if (styleManagerRef) { auto styleManager = context->getService(styleManagerRef); if (styleManager->GetStyle().name == "Dark") { return QmitkChartWidget::ColorTheme::darkstyle; } else { return QmitkChartWidget::ColorTheme::lightstyle; } } return QmitkChartWidget::ColorTheme::darkstyle; } void QmitkImageStatisticsView::ResetGUI() { m_Controls.widget_statistics->Reset(); m_Controls.widget_statistics->setEnabled(false); m_Controls.widget_histogram->Reset(); m_Controls.widget_histogram->setEnabled(false); m_Controls.widget_histogram->SetTheme(GetColorTheme()); } void QmitkImageStatisticsView::OnGenerationStarted(const mitk::DataNode* /*imageNode*/, const mitk::DataNode* /*roiNode*/, const QmitkDataGenerationJobBase* /*job*/) { m_Controls.label_currentlyComputingStatistics->setVisible(true); } void QmitkImageStatisticsView::OnGenerationFinished() { m_Controls.label_currentlyComputingStatistics->setVisible(false); mitk::StatusBar::GetInstance()->Clear(); this->UpdateIntensityProfile(); this->UpdateHistogramWidget(); } void QmitkImageStatisticsView::OnSelectedTimePointChanged(const mitk::TimePointType& /*newTimePoint*/) { this->UpdateHistogramWidget(); } void QmitkImageStatisticsView::OnJobError(QString error, const QmitkDataGenerationJobBase* /*failedJob*/) { mitk::StatusBar::GetInstance()->DisplayErrorText(error.toStdString().c_str()); MITK_WARN << "Error when calculating statistics: " << error; } void QmitkImageStatisticsView::OnRequestHistogramUpdate(unsigned int nbins) { m_Controls.widget_statistics->SetHistogramNBins(nbins); m_DataGenerator->SetHistogramNBins(nbins); this->UpdateIntensityProfile(); this->UpdateHistogramWidget(); } void QmitkImageStatisticsView::OnCheckBoxIgnoreZeroStateChanged(int state) { auto ignoreZeroValueVoxel = (state == Qt::Unchecked) ? false : true; m_Controls.widget_statistics->SetIgnoreZeroValueVoxel(ignoreZeroValueVoxel); m_DataGenerator->SetIgnoreZeroValueVoxel(ignoreZeroValueVoxel); this->UpdateIntensityProfile(); this->UpdateHistogramWidget(); } void QmitkImageStatisticsView::OnImageSelectionChanged(QmitkAbstractNodeSelectionWidget::NodeList /*nodes*/) { auto images = m_Controls.imageNodesSelector->GetSelectedNodesStdVector(); m_Controls.widget_statistics->SetImageNodes(images); m_Controls.widget_statistics->setEnabled(!images.empty()); m_Controls.roiNodesSelector->SetNodePredicate(this->GenerateROIPredicate()); m_DataGenerator->SetAutoUpdate(false); m_DataGenerator->SetImageNodes(images); m_DataGenerator->Generate(); m_DataGenerator->SetAutoUpdate(true); this->UpdateHistogramWidget(); this->UpdateIntensityProfile(); } void QmitkImageStatisticsView::OnROISelectionChanged(QmitkAbstractNodeSelectionWidget::NodeList /*nodes*/) { auto rois = m_Controls.roiNodesSelector->GetSelectedNodesStdVector(); m_Controls.widget_statistics->SetMaskNodes(rois); m_DataGenerator->SetAutoUpdate(false); m_DataGenerator->SetROINodes(rois); m_DataGenerator->Generate(); m_DataGenerator->SetAutoUpdate(true); this->UpdateHistogramWidget(); this->UpdateIntensityProfile(); } void QmitkImageStatisticsView::OnButtonSelectionPressed() { QmitkNodeSelectionDialog* dialog = new QmitkNodeSelectionDialog(nullptr, "Select input for the statistic","You may select images and ROIs to compute their statistic. ROIs may be segmentations or planar figures."); dialog->SetDataStorage(GetDataStorage()); dialog->SetSelectionCheckFunction(CheckForSameGeometry()); // set predicates auto isPlanarFigurePredicate = mitk::GetImageStatisticsPlanarFigurePredicate(); auto isMaskPredicate = mitk::GetImageStatisticsMaskPredicate(); auto isImagePredicate = mitk::GetImageStatisticsImagePredicate(); auto isMaskOrPlanarFigurePredicate = mitk::NodePredicateOr::New(isPlanarFigurePredicate, isMaskPredicate); auto isImageOrMaskOrPlanarFigurePredicate = mitk::NodePredicateOr::New(isMaskOrPlanarFigurePredicate, isImagePredicate); dialog->SetNodePredicate(isImageOrMaskOrPlanarFigurePredicate); dialog->SetSelectionMode(QAbstractItemView::MultiSelection); dialog->SetCurrentSelection(m_Controls.imageNodesSelector->GetSelectedNodes()+m_Controls.roiNodesSelector->GetSelectedNodes()); if (dialog->exec()) { auto selectedNodeList = dialog->GetSelectedNodes(); m_Controls.imageNodesSelector->SetCurrentSelection(selectedNodeList); m_Controls.roiNodesSelector->SetCurrentSelection(selectedNodeList); } delete dialog; } QmitkNodeSelectionDialog::SelectionCheckFunctionType QmitkImageStatisticsView::CheckForSameGeometry() const { auto isMaskPredicate = mitk::GetImageStatisticsMaskPredicate(); auto lambda = [isMaskPredicate](const QmitkNodeSelectionDialog::NodeList& nodes) { if (nodes.empty()) { return std::string(); } const mitk::Image* imageNodeData = nullptr; for (auto& node : nodes) { auto castedData = dynamic_cast(node->GetData()); if (castedData != nullptr && !isMaskPredicate->CheckNode(node)) { imageNodeData = castedData; break; } } if (imageNodeData == nullptr) { std::stringstream ss; ss << "

Select at least one image.

"; return ss.str(); } auto imageGeoPredicate = mitk::NodePredicateGeometry::New(imageNodeData->GetGeometry()); auto maskGeoPredicate = mitk::NodePredicateSubGeometry::New(imageNodeData->GetGeometry()); for (auto& rightNode : nodes) { if (imageNodeData != rightNode->GetData()) { bool validGeometry = true; if (isMaskPredicate->CheckNode(rightNode)) { validGeometry = maskGeoPredicate->CheckNode(rightNode); } else if (dynamic_cast(rightNode->GetData())) { validGeometry = imageGeoPredicate->CheckNode(rightNode); } else { const mitk::PlanarFigure* planar2 = dynamic_cast(rightNode->GetData()); if (planar2) { validGeometry = mitk::PlanarFigureMaskGenerator::CheckPlanarFigureIsNotTilted(planar2->GetPlaneGeometry(), imageNodeData->GetGeometry()); } } if (!validGeometry) { std::stringstream ss; ss << "

Invalid selection: All selected nodes must have the same geometry.

Differing node i.a.: \""; ss << rightNode->GetName() <<"\"

"; return ss.str(); } } } return std::string(); }; return lambda; } mitk::NodePredicateBase::Pointer QmitkImageStatisticsView::GenerateROIPredicate() const { auto isPlanarFigurePredicate = mitk::GetImageStatisticsPlanarFigurePredicate(); auto isMaskPredicate = mitk::GetImageStatisticsMaskPredicate(); auto isMaskOrPlanarFigurePredicate = mitk::NodePredicateOr::New(isPlanarFigurePredicate, isMaskPredicate); mitk::NodePredicateBase::Pointer result = isMaskOrPlanarFigurePredicate.GetPointer(); if(!m_Controls.imageNodesSelector->GetSelectedNodes().empty()) { auto image = m_Controls.imageNodesSelector->GetSelectedNodes().front()->GetData(); auto imageGeoPredicate = mitk::NodePredicateSubGeometry::New(image->GetGeometry()); auto lambda = [image, imageGeoPredicate](const mitk::DataNode* node) { bool sameGeometry = true; if (dynamic_cast(node->GetData()) != nullptr) { sameGeometry = imageGeoPredicate->CheckNode(node); } else { const auto planar2 = dynamic_cast(node->GetData()); if (planar2) { sameGeometry = mitk::PlanarFigureMaskGenerator::CheckPlanarFigureIsNotTilted(planar2->GetPlaneGeometry(), image->GetGeometry()); } } return sameGeometry; }; result = mitk::NodePredicateAnd::New(isMaskOrPlanarFigurePredicate, mitk::NodePredicateFunction::New(lambda)).GetPointer(); } return result; }