diff --git a/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp b/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp index eba6589fc8..f16f0683b3 100644 --- a/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp +++ b/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp @@ -1,719 +1,722 @@ /*=================================================================== 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 "mitkStandardFileLocations.h" #include "mitkDicomSeriesReader.h" #include "mitkTestingMacros.h" #include "mitkImageStatisticsCalculator.h" #include "mitkPlanarPolygon.h" #include "mitkDicomSeriesReader.h" #include #include "vtkStreamingDemandDrivenPipeline.h" #include #include #include "itkImage.h" #include #include #include //#include /** * \brief Test class for mitkImageStatisticsCalculator * * This test covers: * - instantiation of an ImageStatisticsCalculator class * - correctness of statistics when using PlanarFigures for masking */ class mitkImageStatisticsCalculatorTestClass { public: struct testCase { int id; mitk::PlanarFigure::Pointer figure; double mean; double sd; }; // calculate statistics for the given image and planarpolygon static const mitk::ImageStatisticsCalculator::Statistics TestStatistics( mitk::Image::Pointer image, mitk::PlanarFigure::Pointer polygon ) { mitk::ImageStatisticsCalculator::Pointer statisticsCalculator = mitk::ImageStatisticsCalculator::New(); statisticsCalculator->SetImage( image ); statisticsCalculator->SetMaskingModeToPlanarFigure(); statisticsCalculator->SetPlanarFigure( polygon ); statisticsCalculator->ComputeStatistics(); return statisticsCalculator->GetStatistics(); } // returns a vector of defined test-cases static std::vector InitializeTestCases( mitk::Geometry2D::Pointer geom ) { std::vector testCases; { /***************************** * one whole white pixel * -> mean of 255 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 10.5 ; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 10.5; pnt4[1] = 4.5; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 255.0; test.sd = 0.0; testCases.push_back( test ); } { /***************************** * half pixel in x-direction (white) * -> mean of 255 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 10.0 ; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 10.0; pnt4[1] = 4.5; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 255.0; test.sd = 0.0; testCases.push_back( test ); } { /***************************** * half pixel in diagonal-direction (white) * -> mean of 255 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 10.5 ; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5; figure1->SetControlPoint( 2, pnt3, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 255.0; test.sd = 0.0; testCases.push_back( test ); } { /***************************** * one pixel (white) + 2 half pixels (white) + 1 half pixel (black) * -> mean of 191.25 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 1.1; pnt1[1] = 1.1; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 2.0; pnt2[1] = 2.0; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 3.0; pnt3[1] = 1.0; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 2.0; pnt4[1] = 0.0; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 191.25; test.sd = 127.5; testCases.push_back( test ); } { /***************************** * whole pixel (white) + half pixel (gray) in x-direction * -> mean of 191.5 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.5; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 191.50; test.sd = 89.80; testCases.push_back( test ); } { /***************************** * quarter pixel (black) + whole pixel (white) + half pixel (gray) in x-direction * -> mean of 191.5 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.25; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.25; pnt3[1] = 4.5; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.5; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 191.5; test.sd = 89.80; testCases.push_back( test ); } { /***************************** * half pixel (black) + whole pixel (white) + half pixel (gray) in x-direction * -> mean of 127.66 expected ******************************/ mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New(); figure1->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5; figure1->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.0; pnt2[1] = 3.5; figure1->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 9.0; pnt3[1] = 4.0; figure1->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.0; figure1->SetControlPoint( 3, pnt4, true ); figure1->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure1; test.mean = 127.66; test.sd = 127.5; testCases.push_back( test ); } { /***************************** * whole pixel (gray) * -> mean of 128 expected ******************************/ mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New(); figure2->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5; figure2->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 11.5; figure2->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 11.5; figure2->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5; figure2->SetControlPoint( 3, pnt4, true ); figure2->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure2; test.mean = 128.0; test.sd = 0.0; testCases.push_back( test ); } { /***************************** * whole pixel (gray) + half pixel (white) in y-direction * -> mean of 191.5 expected ******************************/ mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New(); figure2->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5; figure2->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 12.0; figure2->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 12.0; figure2->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5; figure2->SetControlPoint( 3, pnt4, true ); figure2->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure2; test.mean = 191.5; test.sd = 89.80; testCases.push_back( test ); } { /***************************** * 2 whole pixel (white) + 2 whole pixel (black) in y-direction * -> mean of 127.66 expected ******************************/ mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New(); figure2->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5; figure2->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 13.5; figure2->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 13.5; figure2->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5; figure2->SetControlPoint( 3, pnt4, true ); figure2->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure2; test.mean = 127.66; test.sd = 127.5; testCases.push_back( test ); } { /***************************** * 9 whole pixels (white) + 3 half pixels (white) * + 3 whole pixel (black) [ + 3 slightly less than half pixels (black)] * -> mean of 204.0 expected ******************************/ mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New(); figure2->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 0.5; pnt1[1] = 0.5; figure2->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 3.5; pnt2[1] = 3.5; figure2->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 8.4999; pnt3[1] = 3.5; figure2->SetControlPoint( 2, pnt3, true ); mitk::Point2D pnt4; pnt4[0] = 5.4999; pnt4[1] = 0.5; figure2->SetControlPoint( 3, pnt4, true ); figure2->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure2; test.mean = 204.0; test.sd = 105.58; testCases.push_back( test ); } { /***************************** * half pixel (white) + whole pixel (white) + half pixel (black) * -> mean of 212.66 expected ******************************/ mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New(); figure2->SetGeometry2D( geom ); mitk::Point2D pnt1; pnt1[0] = 9.5; pnt1[1] = 0.5; figure2->PlaceFigure( pnt1 ); mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 2.5; figure2->SetControlPoint( 1, pnt2, true ); mitk::Point2D pnt3; pnt3[0] = 11.5; pnt3[1] = 2.5; figure2->SetControlPoint( 2, pnt3, true ); figure2->GetPolyLine(0); testCase test; test.id = testCases.size(); test.figure = figure2; test.mean = 212.66; test.sd = 73.32; testCases.push_back( test ); } return testCases; } static void GetTestConvolutionMask(itk::Image< float, 2 > *mask, double RadiusInMM) { /***************************** * radius of 2.5 mm * -> expected ConvolutionMask: * 0,25 0,75 1 0,75 0,25 * 0,75 1 1 1 0,75 * 1 1 1 1 1 * 0,75 1 1 1 0,75 * 0,25 0,75 1 0,75 0,25 ******************************/ typedef itk::Image ImageType; ImageType::Pointer convolutionMask = ImageType::New(); ImageType::RegionType region; ImageType::IndexType start; ImageType::SizeType size; ImageType::IndexType pixelIndex; ImageType::SpacingType spacing; ImageType::IndexType origin; for(unsigned int i = 0; i < 2; ++i) { spacing[i] = 1.0; start[i] = 0.0; double countIndex = 2.0 * RadiusInMM / spacing[i]; //Rounding up to the next integer by cast countIndex += 0.9; int castedIndex = static_cast(countIndex); //We always have an uneven number in size to determine a center-point in the convolution mask if(castedIndex % 2 > 0 ) { size[i] = castedIndex; } else { size[i] = castedIndex +1; } } region.SetSize(size); region.SetIndex(start); convolutionMask->SetRegions(region); convolutionMask->SetSpacing(spacing); convolutionMask->Allocate(); //y = 0 pixelIndex[0] = 0; pixelIndex[1] = 0; convolutionMask->SetPixel(pixelIndex, 0.25); pixelIndex[0] = 1; pixelIndex[1] = 0; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 2; pixelIndex[1] = 0; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 3; pixelIndex[1] = 0; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 4; pixelIndex[1] = 0; convolutionMask->SetPixel(pixelIndex, 0.25); //y = 1 pixelIndex[1] = 0; pixelIndex[1] = 1; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 1; pixelIndex[1] = 1; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 2; pixelIndex[1] = 1; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 3; pixelIndex[1] = 1; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 4; pixelIndex[1] = 1; convolutionMask->SetPixel(pixelIndex, 0.75); //y = 2 pixelIndex[1] = 0; pixelIndex[1] = 2; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 1; pixelIndex[1] = 2; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 2; pixelIndex[1] = 2; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 3; pixelIndex[1] = 2; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 4; pixelIndex[1] = 2; convolutionMask->SetPixel(pixelIndex, 1.0); //y = 3 pixelIndex[1] = 0; pixelIndex[1] = 3; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 1; pixelIndex[1] = 3; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 2; pixelIndex[1] = 3; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 3; pixelIndex[1] = 3; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 4; pixelIndex[1] = 3; convolutionMask->SetPixel(pixelIndex, 0.75); //y = 4 pixelIndex[1] = 0; pixelIndex[1] = 4; convolutionMask->SetPixel(pixelIndex, 0.25); pixelIndex[0] = 1; pixelIndex[1] = 4; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 2; pixelIndex[1] = 4; convolutionMask->SetPixel(pixelIndex, 1.0); pixelIndex[0] = 3; pixelIndex[1] = 4; convolutionMask->SetPixel(pixelIndex, 0.75); pixelIndex[0] = 4; pixelIndex[1] = 4; convolutionMask->SetPixel(pixelIndex, 0.25); typedef itk::ImageRegionConstIteratorWithIndex IteratorType; IteratorType it(convolutionMask, convolutionMask->GetLargestPossibleRegion()); std::cout << std::endl << std::endl; std::cout << "Selbsterzeugtes Bild: "<< std::endl; //#ifdef DEBUG_SEGMENTATION_CORRECTION // Debug Ausgabe: unsigned int lastZ = 1000000000; unsigned int lastY = 1000000000; for(it.GoToBegin(); !it.IsAtEnd(); ++it) { double x = it.Get(); if (it.GetIndex()[1] != lastY) { std::cout << std::endl; lastY = it.GetIndex()[1]; } if (it.GetIndex()[0] != lastZ) { std::cout << x << " "; lastZ = it.GetIndex()[0]; } } //#endif typedef itk::SimilarityIndexImageFilter FilterType; FilterType::Pointer similiarityFilter = FilterType::New(); similiarityFilter->SetInput1(mask); similiarityFilter->SetInput2(convolutionMask); similiarityFilter->Update(); ImageType::Pointer similarityImage = similiarityFilter->GetOutput(); IteratorType iterator(similarityImage, similarityImage->GetLargestPossibleRegion()); std::cout << "Bild nach Filter: "<< std::endl; //#ifdef DEBUG_SEGMENTATION_CORRECTION // Debug Ausgabe: lastZ = 1000000000; lastY = 1000000000; for(iterator.GoToBegin(); !iterator.IsAtEnd(); ++iterator) { double x = iterator.Get(); if (iterator.GetIndex()[1] != lastY) { std::cout << std::endl; lastY = iterator.GetIndex()[1]; } if (iterator.GetIndex()[0] != lastZ) { std::cout << x << " "; lastZ = iterator.GetIndex()[0]; } } //#endif } // loads the test image static mitk::Image::Pointer GetTestImage() { mitk::StandardFileLocations::Pointer locator = mitk::StandardFileLocations::GetInstance(); const std::string filename = locator->FindFile("testimage.dcm", "Modules/MitkExt/Testing/Data"); if (filename.empty()) { MITK_ERROR << "Could not find test file"; return NULL; } else { MITK_INFO << "Found testimage.dcm"; } itk::FilenamesContainer file; file.push_back( filename ); mitk::DicomSeriesReader* reader = new mitk::DicomSeriesReader; mitk::DataNode::Pointer node = reader->LoadDicomSeries( file, false, false ); mitk::Image::Pointer image = dynamic_cast( node->GetData() ); return image; } }; int TestUnitilizedImage() { /***************************** * loading uninitialized image to datastorage ******************************/ std::cout << "Testing loading uninitialized image to datastorage:"; try{ MITK_TEST_FOR_EXCEPTION_BEGIN(mitk::Exception) mitk::Image::Pointer image = mitk::Image::New(); mitk::DataNode::Pointer node = mitk::DataNode::New(); node->SetData(image); mitk::ImageStatisticsCalculator::Pointer is = mitk::ImageStatisticsCalculator::New(); is->ComputeStatistics(); MITK_TEST_FOR_EXCEPTION_END(mitk::Exception) } catch (const mitk::Exception&) { std::cout << "Success: Loading uninitialized image has thrown an exception." << std::endl; } return 0; } int mitkImageStatisticsCalculatorTest(int, char* []) { // always start with this! MITK_TEST_BEGIN("mitkImageStatisticsCalculatorTest") //QCoreApplication app(argc, argv); mitk::Image::Pointer image = mitkImageStatisticsCalculatorTestClass::GetTestImage(); MITK_TEST_CONDITION_REQUIRED( image.IsNotNull(), "Loading test image" ); mitk::Geometry2D::Pointer geom = image->GetSlicedGeometry()->GetGeometry2D(0); std::vector allTestCases = mitkImageStatisticsCalculatorTestClass::InitializeTestCases( geom ); for ( std::vector::size_type i=0; i formuliert verschiedene TestFälle: Polygon und Masken (Segmentierung) + TestUnitilizedImage(); MITK_TEST_END() } diff --git a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp index 7de6070eef..9242aa12e0 100644 --- a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp +++ b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp @@ -1,1553 +1,1532 @@ /*=================================================================== 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 "mitkImageStatisticsCalculator.h" #include "mitkImageAccessByItk.h" #include "mitkImageCast.h" #include "mitkExtractImageFilter.h" #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #define _USE_MATH_DEFINES #include #if ( ( VTK_MAJOR_VERSION <= 5 ) && ( VTK_MINOR_VERSION<=8) ) #include "mitkvtkLassoStencilSource.h" #else #include "vtkLassoStencilSource.h" #endif #include #include namespace mitk { ImageStatisticsCalculator::ImageStatisticsCalculator() : m_MaskingMode( MASKING_MODE_NONE ), m_MaskingModeChanged( false ), m_IgnorePixelValue(0.0), m_DoIgnorePixelValue(false), m_IgnorePixelValueChanged(false), m_PlanarFigureAxis (0), m_PlanarFigureSlice (0), m_PlanarFigureCoordinate0 (0), m_PlanarFigureCoordinate1 (0) { m_EmptyHistogram = HistogramType::New(); m_EmptyHistogram->SetMeasurementVectorSize(1); HistogramType::SizeType histogramSize(1); histogramSize.Fill( 256 ); m_EmptyHistogram->Initialize( histogramSize ); m_EmptyStatistics.Reset(); } ImageStatisticsCalculator::~ImageStatisticsCalculator() { } void ImageStatisticsCalculator::SetImage( const mitk::Image *image ) { if ( m_Image != image ) { m_Image = image; this->Modified(); unsigned int numberOfTimeSteps = image->GetTimeSteps(); // Initialize vectors to time-size of this image m_ImageHistogramVector.resize( numberOfTimeSteps ); m_MaskedImageHistogramVector.resize( numberOfTimeSteps ); m_PlanarFigureHistogramVector.resize( numberOfTimeSteps ); m_ImageStatisticsVector.resize( numberOfTimeSteps ); m_MaskedImageStatisticsVector.resize( numberOfTimeSteps ); m_PlanarFigureStatisticsVector.resize( numberOfTimeSteps ); m_ImageStatisticsTimeStampVector.resize( numberOfTimeSteps ); m_MaskedImageStatisticsTimeStampVector.resize( numberOfTimeSteps ); m_PlanarFigureStatisticsTimeStampVector.resize( numberOfTimeSteps ); m_ImageStatisticsCalculationTriggerVector.resize( numberOfTimeSteps ); m_MaskedImageStatisticsCalculationTriggerVector.resize( numberOfTimeSteps ); m_PlanarFigureStatisticsCalculationTriggerVector.resize( numberOfTimeSteps ); for ( unsigned int t = 0; t < image->GetTimeSteps(); ++t ) { m_ImageStatisticsTimeStampVector[t].Modified(); m_ImageStatisticsCalculationTriggerVector[t] = true; } } } void ImageStatisticsCalculator::SetImageMask( const mitk::Image *imageMask ) { if ( m_Image.IsNull() ) { itkExceptionMacro( << "Image needs to be set first!" ); } if ( m_Image->GetTimeSteps() != imageMask->GetTimeSteps() ) { itkExceptionMacro( << "Image and image mask need to have equal number of time steps!" ); } if ( m_ImageMask != imageMask ) { m_ImageMask = imageMask; this->Modified(); for ( unsigned int t = 0; t < m_Image->GetTimeSteps(); ++t ) { m_MaskedImageStatisticsTimeStampVector[t].Modified(); m_MaskedImageStatisticsCalculationTriggerVector[t] = true; } } } void ImageStatisticsCalculator::SetPlanarFigure( mitk::PlanarFigure *planarFigure ) { if ( m_Image.IsNull() ) { itkExceptionMacro( << "Image needs to be set first!" ); } if ( m_PlanarFigure != planarFigure ) { m_PlanarFigure = planarFigure; this->Modified(); for ( unsigned int t = 0; t < m_Image->GetTimeSteps(); ++t ) { m_PlanarFigureStatisticsTimeStampVector[t].Modified(); m_PlanarFigureStatisticsCalculationTriggerVector[t] = true; } } } void ImageStatisticsCalculator::SetMaskingMode( unsigned int mode ) { if ( m_MaskingMode != mode ) { m_MaskingMode = mode; m_MaskingModeChanged = true; this->Modified(); } } void ImageStatisticsCalculator::SetMaskingModeToNone() { if ( m_MaskingMode != MASKING_MODE_NONE ) { m_MaskingMode = MASKING_MODE_NONE; m_MaskingModeChanged = true; this->Modified(); } } void ImageStatisticsCalculator::SetMaskingModeToImage() { if ( m_MaskingMode != MASKING_MODE_IMAGE ) { m_MaskingMode = MASKING_MODE_IMAGE; m_MaskingModeChanged = true; this->Modified(); } } void ImageStatisticsCalculator::SetMaskingModeToPlanarFigure() { if ( m_MaskingMode != MASKING_MODE_PLANARFIGURE ) { m_MaskingMode = MASKING_MODE_PLANARFIGURE; m_MaskingModeChanged = true; this->Modified(); } } void ImageStatisticsCalculator::SetIgnorePixelValue(double value) { if ( m_IgnorePixelValue != value ) { m_IgnorePixelValue = value; if(m_DoIgnorePixelValue) { m_IgnorePixelValueChanged = true; } this->Modified(); } } double ImageStatisticsCalculator::GetIgnorePixelValue() { return m_IgnorePixelValue; } void ImageStatisticsCalculator::SetDoIgnorePixelValue(bool value) { if ( m_DoIgnorePixelValue != value ) { m_DoIgnorePixelValue = value; m_IgnorePixelValueChanged = true; this->Modified(); } } bool ImageStatisticsCalculator::GetDoIgnorePixelValue() { return m_DoIgnorePixelValue; } void ImageStatisticsCalculator::SetHotspotSize(double value) { m_HotspotSize = (4/3) * M_PI * value * value * value; } double ImageStatisticsCalculator::GetHotspotSize() { return m_HotspotSize; } void ImageStatisticsCalculator::SetCalculateHotspot(bool value) { m_CalculateHotspot = value; } bool ImageStatisticsCalculator::IsHotspotCalculated() { return m_CalculateHotspot; } bool ImageStatisticsCalculator::ComputeStatistics( unsigned int timeStep ) { if (m_Image.IsNull() ) { mitkThrow() << "Image not set!"; } if (!m_Image->IsInitialized()) { mitkThrow() << "Image not initialized!"; } if ( m_Image->GetReferenceCount() == 1 ) { // Image no longer valid; we are the only ones to still hold a reference on it return false; } if ( timeStep >= m_Image->GetTimeSteps() ) { throw std::runtime_error( "Error: invalid time step!" ); } // If a mask was set but we are the only ones to still hold a reference on // it, delete it. if ( m_ImageMask.IsNotNull() && (m_ImageMask->GetReferenceCount() == 1) ) { m_ImageMask = NULL; } // Check if statistics is already up-to-date unsigned long imageMTime = m_ImageStatisticsTimeStampVector[timeStep].GetMTime(); unsigned long maskedImageMTime = m_MaskedImageStatisticsTimeStampVector[timeStep].GetMTime(); unsigned long planarFigureMTime = m_PlanarFigureStatisticsTimeStampVector[timeStep].GetMTime(); bool imageStatisticsCalculationTrigger = m_ImageStatisticsCalculationTriggerVector[timeStep]; bool maskedImageStatisticsCalculationTrigger = m_MaskedImageStatisticsCalculationTriggerVector[timeStep]; bool planarFigureStatisticsCalculationTrigger = m_PlanarFigureStatisticsCalculationTriggerVector[timeStep]; if ( !m_IgnorePixelValueChanged && ((m_MaskingMode != MASKING_MODE_NONE) || (imageMTime > m_Image->GetMTime() && !imageStatisticsCalculationTrigger)) && ((m_MaskingMode != MASKING_MODE_IMAGE) || (maskedImageMTime > m_ImageMask->GetMTime() && !maskedImageStatisticsCalculationTrigger)) && ((m_MaskingMode != MASKING_MODE_PLANARFIGURE) || (planarFigureMTime > m_PlanarFigure->GetMTime() && !planarFigureStatisticsCalculationTrigger)) ) { // Statistics is up to date! if ( m_MaskingModeChanged ) { m_MaskingModeChanged = false; return true; } else { return false; } } // Reset state changed flag m_MaskingModeChanged = false; m_IgnorePixelValueChanged = false; // Depending on masking mode, extract and/or generate the required image // and mask data from the user input this->ExtractImageAndMask( timeStep ); StatisticsContainer *statisticsContainer; HistogramContainer *histogramContainer; switch ( m_MaskingMode ) { case MASKING_MODE_NONE: default: if(!m_DoIgnorePixelValue) { statisticsContainer = &m_ImageStatisticsVector[timeStep]; histogramContainer = &m_ImageHistogramVector[timeStep]; m_ImageStatisticsTimeStampVector[timeStep].Modified(); m_ImageStatisticsCalculationTriggerVector[timeStep] = false; } else { statisticsContainer = &m_MaskedImageStatisticsVector[timeStep]; histogramContainer = &m_MaskedImageHistogramVector[timeStep]; m_MaskedImageStatisticsTimeStampVector[timeStep].Modified(); m_MaskedImageStatisticsCalculationTriggerVector[timeStep] = false; } break; case MASKING_MODE_IMAGE: statisticsContainer = &m_MaskedImageStatisticsVector[timeStep]; histogramContainer = &m_MaskedImageHistogramVector[timeStep]; m_MaskedImageStatisticsTimeStampVector[timeStep].Modified(); m_MaskedImageStatisticsCalculationTriggerVector[timeStep] = false; break; case MASKING_MODE_PLANARFIGURE: statisticsContainer = &m_PlanarFigureStatisticsVector[timeStep]; histogramContainer = &m_PlanarFigureHistogramVector[timeStep]; m_PlanarFigureStatisticsTimeStampVector[timeStep].Modified(); m_PlanarFigureStatisticsCalculationTriggerVector[timeStep] = false; break; } // Calculate statistics and histogram(s) if ( m_InternalImage->GetDimension() == 3 ) { if ( m_MaskingMode == MASKING_MODE_NONE && !m_DoIgnorePixelValue ) { AccessFixedDimensionByItk_2( m_InternalImage, InternalCalculateStatisticsUnmasked, 3, statisticsContainer, histogramContainer ); } else { AccessFixedDimensionByItk_3( m_InternalImage, InternalCalculateStatisticsMasked, 3, m_InternalImageMask3D.GetPointer(), statisticsContainer, histogramContainer ); } } else if ( m_InternalImage->GetDimension() == 2 ) { if ( m_MaskingMode == MASKING_MODE_NONE && !m_DoIgnorePixelValue ) { AccessFixedDimensionByItk_2( m_InternalImage, InternalCalculateStatisticsUnmasked, 2, statisticsContainer, histogramContainer ); } else { AccessFixedDimensionByItk_3( m_InternalImage, InternalCalculateStatisticsMasked, 2, m_InternalImageMask2D.GetPointer(), statisticsContainer, histogramContainer ); } } else { MITK_ERROR << "ImageStatistics: Image dimension not supported!"; } // Release unused image smart pointers to free memory m_InternalImage = mitk::Image::ConstPointer(); m_InternalImageMask3D = MaskImage3DType::Pointer(); m_InternalImageMask2D = MaskImage2DType::Pointer(); return true; } const ImageStatisticsCalculator::HistogramType * ImageStatisticsCalculator::GetHistogram( unsigned int timeStep, unsigned int label ) const { if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) ) { return NULL; } switch ( m_MaskingMode ) { case MASKING_MODE_NONE: default: { if(m_DoIgnorePixelValue) return m_MaskedImageHistogramVector[timeStep][label]; return m_ImageHistogramVector[timeStep][label]; } case MASKING_MODE_IMAGE: return m_MaskedImageHistogramVector[timeStep][label]; case MASKING_MODE_PLANARFIGURE: return m_PlanarFigureHistogramVector[timeStep][label]; } } const ImageStatisticsCalculator::HistogramContainer & ImageStatisticsCalculator::GetHistogramVector( unsigned int timeStep ) const { if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) ) { return m_EmptyHistogramContainer; } switch ( m_MaskingMode ) { case MASKING_MODE_NONE: default: { if(m_DoIgnorePixelValue) return m_MaskedImageHistogramVector[timeStep]; return m_ImageHistogramVector[timeStep]; } case MASKING_MODE_IMAGE: return m_MaskedImageHistogramVector[timeStep]; case MASKING_MODE_PLANARFIGURE: return m_PlanarFigureHistogramVector[timeStep]; } } const ImageStatisticsCalculator::Statistics & ImageStatisticsCalculator::GetStatistics( unsigned int timeStep, unsigned int label ) const { if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) ) { return m_EmptyStatistics; } switch ( m_MaskingMode ) { case MASKING_MODE_NONE: default: { if(m_DoIgnorePixelValue) return m_MaskedImageStatisticsVector[timeStep][label]; return m_ImageStatisticsVector[timeStep][label]; } case MASKING_MODE_IMAGE: return m_MaskedImageStatisticsVector[timeStep][label]; case MASKING_MODE_PLANARFIGURE: return m_PlanarFigureStatisticsVector[timeStep][label]; } } const ImageStatisticsCalculator::Statistics & ImageStatisticsCalculator::GetHotspotStatistics( unsigned int timeStep, unsigned int label) const { if(m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) ) return m_EmptyStatistics; return m_MaskedImageHotspotStatisticsVector[timeStep][label]; } const ImageStatisticsCalculator::StatisticsContainer & ImageStatisticsCalculator::GetStatisticsVector( unsigned int timeStep ) const { if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) ) { return m_EmptyStatisticsContainer; } switch ( m_MaskingMode ) { case MASKING_MODE_NONE: default: { if(m_DoIgnorePixelValue) return m_MaskedImageStatisticsVector[timeStep]; return m_ImageStatisticsVector[timeStep]; } case MASKING_MODE_IMAGE: return m_MaskedImageStatisticsVector[timeStep]; case MASKING_MODE_PLANARFIGURE: return m_PlanarFigureStatisticsVector[timeStep]; } } void ImageStatisticsCalculator::ExtractImageAndMask( unsigned int timeStep ) { if ( m_Image.IsNull() ) { throw std::runtime_error( "Error: image empty!" ); } if ( timeStep >= m_Image->GetTimeSteps() ) { throw std::runtime_error( "Error: invalid time step!" ); } ImageTimeSelector::Pointer imageTimeSelector = ImageTimeSelector::New(); imageTimeSelector->SetInput( m_Image ); imageTimeSelector->SetTimeNr( timeStep ); imageTimeSelector->UpdateLargestPossibleRegion(); mitk::Image *timeSliceImage = imageTimeSelector->GetOutput(); switch ( m_MaskingMode ) { case MASKING_MODE_NONE: { m_InternalImage = timeSliceImage; m_InternalImageMask2D = NULL; m_InternalImageMask3D = NULL; if(m_DoIgnorePixelValue) { if( m_InternalImage->GetDimension() == 3 ) { CastToItkImage( timeSliceImage, m_InternalImageMask3D ); m_InternalImageMask3D->FillBuffer(1); } if( m_InternalImage->GetDimension() == 2 ) { CastToItkImage( timeSliceImage, m_InternalImageMask2D ); m_InternalImageMask2D->FillBuffer(1); } } break; } case MASKING_MODE_IMAGE: { if ( m_ImageMask.IsNotNull() && (m_ImageMask->GetReferenceCount() > 1) ) { if ( timeStep < m_ImageMask->GetTimeSteps() ) { ImageTimeSelector::Pointer maskedImageTimeSelector = ImageTimeSelector::New(); maskedImageTimeSelector->SetInput( m_ImageMask ); maskedImageTimeSelector->SetTimeNr( timeStep ); maskedImageTimeSelector->UpdateLargestPossibleRegion(); mitk::Image *timeSliceMaskedImage = maskedImageTimeSelector->GetOutput(); m_InternalImage = timeSliceImage; CastToItkImage( timeSliceMaskedImage, m_InternalImageMask3D ); } else { throw std::runtime_error( "Error: image mask has not enough time steps!" ); } } else { throw std::runtime_error( "Error: image mask empty!" ); } break; } case MASKING_MODE_PLANARFIGURE: { m_InternalImageMask2D = NULL; if ( m_PlanarFigure.IsNull() ) { throw std::runtime_error( "Error: planar figure empty!" ); } if ( !m_PlanarFigure->IsClosed() ) { throw std::runtime_error( "Masking not possible for non-closed figures" ); } const Geometry3D *imageGeometry = timeSliceImage->GetGeometry(); if ( imageGeometry == NULL ) { throw std::runtime_error( "Image geometry invalid!" ); } const Geometry2D *planarFigureGeometry2D = m_PlanarFigure->GetGeometry2D(); if ( planarFigureGeometry2D == NULL ) { throw std::runtime_error( "Planar-Figure not yet initialized!" ); } const PlaneGeometry *planarFigureGeometry = dynamic_cast< const PlaneGeometry * >( planarFigureGeometry2D ); if ( planarFigureGeometry == NULL ) { throw std::runtime_error( "Non-planar planar figures not supported!" ); } // Find principal direction of PlanarFigure in input image unsigned int axis; if ( !this->GetPrincipalAxis( imageGeometry, planarFigureGeometry->GetNormal(), axis ) ) { throw std::runtime_error( "Non-aligned planar figures not supported!" ); } m_PlanarFigureAxis = axis; // Find slice number corresponding to PlanarFigure in input image MaskImage3DType::IndexType index; imageGeometry->WorldToIndex( planarFigureGeometry->GetOrigin(), index ); unsigned int slice = index[axis]; m_PlanarFigureSlice = slice; // Extract slice with given position and direction from image ExtractImageFilter::Pointer imageExtractor = ExtractImageFilter::New(); imageExtractor->SetInput( timeSliceImage ); imageExtractor->SetSliceDimension( axis ); imageExtractor->SetSliceIndex( slice ); imageExtractor->Update(); m_InternalImage = imageExtractor->GetOutput(); // Compute mask from PlanarFigure AccessFixedDimensionByItk_1( m_InternalImage, InternalCalculateMaskFromPlanarFigure, 2, axis ); } } if(m_DoIgnorePixelValue) { if ( m_InternalImage->GetDimension() == 3 ) { AccessFixedDimensionByItk_1( m_InternalImage, InternalMaskIgnoredPixels, 3, m_InternalImageMask3D.GetPointer() ); } else if ( m_InternalImage->GetDimension() == 2 ) { AccessFixedDimensionByItk_1( m_InternalImage, InternalMaskIgnoredPixels, 2, m_InternalImageMask2D.GetPointer() ); } } } bool ImageStatisticsCalculator::GetPrincipalAxis( const Geometry3D *geometry, Vector3D vector, unsigned int &axis ) { vector.Normalize(); for ( unsigned int i = 0; i < 3; ++i ) { Vector3D axisVector = geometry->GetAxisVector( i ); axisVector.Normalize(); if ( fabs( fabs( axisVector * vector ) - 1.0) < mitk::eps ) { axis = i; return true; } } return false; } template < typename TPixel, unsigned int VImageDimension > void ImageStatisticsCalculator::InternalCalculateStatisticsUnmasked( const itk::Image< TPixel, VImageDimension > *image, StatisticsContainer *statisticsContainer, HistogramContainer* histogramContainer ) { typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::Image< unsigned short, VImageDimension > MaskImageType; typedef typename ImageType::IndexType IndexType; typedef itk::Statistics::ScalarImageToHistogramGenerator< ImageType > HistogramGeneratorType; statisticsContainer->clear(); histogramContainer->clear(); // Progress listening... typedef itk::SimpleMemberCommand< ImageStatisticsCalculator > ITKCommandType; ITKCommandType::Pointer progressListener; progressListener = ITKCommandType::New(); progressListener->SetCallbackFunction( this, &ImageStatisticsCalculator::UnmaskedStatisticsProgressUpdate ); // Issue 100 artificial progress events since ScalarIMageToHistogramGenerator // does not (yet?) support progress reporting this->InvokeEvent( itk::StartEvent() ); for ( unsigned int i = 0; i < 100; ++i ) { this->UnmaskedStatisticsProgressUpdate(); } // Calculate statistics (separate filter) typedef itk::StatisticsImageFilter< ImageType > StatisticsFilterType; typename StatisticsFilterType::Pointer statisticsFilter = StatisticsFilterType::New(); statisticsFilter->SetInput( image ); unsigned long observerTag = statisticsFilter->AddObserver( itk::ProgressEvent(), progressListener ); statisticsFilter->Update(); statisticsFilter->RemoveObserver( observerTag ); this->InvokeEvent( itk::EndEvent() ); // Calculate minimum and maximum typedef itk::MinimumMaximumImageCalculator< ImageType > MinMaxFilterType; typename MinMaxFilterType::Pointer minMaxFilter = MinMaxFilterType::New(); minMaxFilter->SetImage( image ); unsigned long observerTag2 = minMaxFilter->AddObserver( itk::ProgressEvent(), progressListener ); minMaxFilter->Compute(); minMaxFilter->RemoveObserver( observerTag2 ); this->InvokeEvent( itk::EndEvent() ); Statistics statistics; statistics.Reset(); statistics.Label = 1; statistics.N = image->GetBufferedRegion().GetNumberOfPixels(); statistics.Min = statisticsFilter->GetMinimum(); statistics.Max = statisticsFilter->GetMaximum(); statistics.Mean = statisticsFilter->GetMean(); statistics.Median = 0.0; statistics.Sigma = statisticsFilter->GetSigma(); statistics.RMS = sqrt( statistics.Mean * statistics.Mean + statistics.Sigma * statistics.Sigma ); statistics.MinIndex.set_size(image->GetImageDimension()); statistics.MaxIndex.set_size(image->GetImageDimension()); for (int i=0; iGetIndexOfMaximum()[i]; statistics.MinIndex[i] = minMaxFilter->GetIndexOfMinimum()[i]; } statisticsContainer->push_back( statistics ); // Calculate histogram typename HistogramGeneratorType::Pointer histogramGenerator = HistogramGeneratorType::New(); histogramGenerator->SetInput( image ); histogramGenerator->SetMarginalScale( 100 ); histogramGenerator->SetNumberOfBins( 768 ); histogramGenerator->SetHistogramMin( statistics.Min ); histogramGenerator->SetHistogramMax( statistics.Max ); histogramGenerator->Compute(); histogramContainer->push_back( histogramGenerator->GetOutput() ); } template < typename TPixel, unsigned int VImageDimension > void ImageStatisticsCalculator::InternalMaskIgnoredPixels( const itk::Image< TPixel, VImageDimension > *image, itk::Image< unsigned short, VImageDimension > *maskImage ) { typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::Image< unsigned short, VImageDimension > MaskImageType; itk::ImageRegionIterator itmask(maskImage, maskImage->GetLargestPossibleRegion()); itk::ImageRegionConstIterator itimage(image, image->GetLargestPossibleRegion()); itmask.GoToBegin(); itimage.GoToBegin(); while( !itmask.IsAtEnd() ) { if(m_IgnorePixelValue == itimage.Get()) { itmask.Set(0); } ++itmask; ++itimage; } } template < typename TPixel, unsigned int VImageDimension > void ImageStatisticsCalculator::InternalCalculateStatisticsMasked( const itk::Image< TPixel, VImageDimension > *image, itk::Image< unsigned short, VImageDimension > *maskImage, StatisticsContainer* statisticsContainer, HistogramContainer* histogramContainer ) { typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::Image< unsigned short, VImageDimension > MaskImageType; typedef typename ImageType::IndexType IndexType; typedef typename ImageType::PointType PointType; typedef typename ImageType::SpacingType SpacingType; typedef itk::LabelStatisticsImageFilter< ImageType, MaskImageType > LabelStatisticsFilterType; typedef itk::ChangeInformationImageFilter< MaskImageType > ChangeInformationFilterType; typedef itk::ExtractImageFilter< ImageType, ImageType > ExtractImageFilterType; statisticsContainer->clear(); histogramContainer->clear(); // Make sure that mask is set if ( maskImage == NULL ) { itkExceptionMacro( << "Mask image needs to be set!" ); } // Make sure that spacing of mask and image are the same SpacingType imageSpacing = image->GetSpacing(); SpacingType maskSpacing = maskImage->GetSpacing(); PointType zeroPoint; zeroPoint.Fill( 0.0 ); if ( (zeroPoint + imageSpacing).SquaredEuclideanDistanceTo( (zeroPoint + maskSpacing) ) > mitk::eps ) { itkExceptionMacro( << "Mask needs to have same spacing as image! (Image spacing: " << imageSpacing << "; Mask spacing: " << maskSpacing << ")" ); } // Make sure that orientation of mask and image are the same typedef typename ImageType::DirectionType DirectionType; DirectionType imageDirection = image->GetDirection(); DirectionType maskDirection = maskImage->GetDirection(); for( int i = 0; i < imageDirection.ColumnDimensions; ++i ) { for( int j = 0; j < imageDirection.ColumnDimensions; ++j ) { double differenceDirection = imageDirection[i][j] - maskDirection[i][j]; if ( fabs( differenceDirection ) > mitk::eps ) { itkExceptionMacro( << "Mask needs to have same direction as image! (Image direction: " << imageDirection << "; Mask direction: " << maskDirection << ")" ); } } } // Make sure that the voxels of mask and image are correctly "aligned", i.e., voxel boundaries are the same in both images PointType imageOrigin = image->GetOrigin(); PointType maskOrigin = maskImage->GetOrigin(); long offset[ImageType::ImageDimension]; typedef itk::ContinuousIndex ContinousIndexType; ContinousIndexType maskOriginContinousIndex, imageOriginContinousIndex; image->TransformPhysicalPointToContinuousIndex(maskOrigin, maskOriginContinousIndex); image->TransformPhysicalPointToContinuousIndex(imageOrigin, imageOriginContinousIndex); for ( unsigned int i = 0; i < ImageType::ImageDimension; ++i ) { double misalignment = maskOriginContinousIndex[i] - floor( maskOriginContinousIndex[i] + 0.5 ); if ( fabs( misalignment ) > mitk::eps ) { itkExceptionMacro( << "Pixels/voxels of mask and image are not sufficiently aligned! (Misalignment: " << misalignment << ")" ); } double indexCoordDistance = maskOriginContinousIndex[i] - imageOriginContinousIndex[i]; offset[i] = (int) indexCoordDistance + image->GetBufferedRegion().GetIndex()[i]; } // Adapt the origin and region (index/size) of the mask so that the origin of both are the same typename ChangeInformationFilterType::Pointer adaptMaskFilter; adaptMaskFilter = ChangeInformationFilterType::New(); adaptMaskFilter->ChangeOriginOn(); adaptMaskFilter->ChangeRegionOn(); adaptMaskFilter->SetInput( maskImage ); adaptMaskFilter->SetOutputOrigin( image->GetOrigin() ); adaptMaskFilter->SetOutputOffset( offset ); adaptMaskFilter->Update(); typename MaskImageType::Pointer adaptedMaskImage = adaptMaskFilter->GetOutput(); // Make sure that mask region is contained within image region if ( !image->GetLargestPossibleRegion().IsInside( adaptedMaskImage->GetLargestPossibleRegion() ) ) { itkExceptionMacro( << "Mask region needs to be inside of image region! (Image region: " << image->GetLargestPossibleRegion() << "; Mask region: " << adaptedMaskImage->GetLargestPossibleRegion() << ")" ); } // If mask region is smaller than image region, extract the sub-sampled region from the original image typename ImageType::SizeType imageSize = image->GetBufferedRegion().GetSize(); typename ImageType::SizeType maskSize = maskImage->GetBufferedRegion().GetSize(); bool maskSmallerImage = false; for ( unsigned int i = 0; i < ImageType::ImageDimension; ++i ) { if ( maskSize[i] < imageSize[i] ) { maskSmallerImage = true; } } typename ImageType::ConstPointer adaptedImage; if ( maskSmallerImage ) { typename ExtractImageFilterType::Pointer extractImageFilter = ExtractImageFilterType::New(); extractImageFilter->SetInput( image ); extractImageFilter->SetExtractionRegion( adaptedMaskImage->GetBufferedRegion() ); extractImageFilter->Update(); adaptedImage = extractImageFilter->GetOutput(); } else { adaptedImage = image; } // Initialize Filter typedef itk::StatisticsImageFilter< ImageType > StatisticsFilterType; typename StatisticsFilterType::Pointer statisticsFilter = StatisticsFilterType::New(); statisticsFilter->SetInput( adaptedImage ); statisticsFilter->Update(); int numberOfBins = ( m_DoIgnorePixelValue && (m_MaskingMode == MASKING_MODE_NONE) ) ? 768 : 384; typename LabelStatisticsFilterType::Pointer labelStatisticsFilter; labelStatisticsFilter = LabelStatisticsFilterType::New(); labelStatisticsFilter->SetInput( adaptedImage ); labelStatisticsFilter->SetLabelInput( adaptedMaskImage ); labelStatisticsFilter->UseHistogramsOn(); labelStatisticsFilter->SetHistogramParameters( numberOfBins, statisticsFilter->GetMinimum(), statisticsFilter->GetMaximum() ); // Add progress listening typedef itk::SimpleMemberCommand< ImageStatisticsCalculator > ITKCommandType; ITKCommandType::Pointer progressListener; progressListener = ITKCommandType::New(); progressListener->SetCallbackFunction( this, &ImageStatisticsCalculator::MaskedStatisticsProgressUpdate ); unsigned long observerTag = labelStatisticsFilter->AddObserver( itk::ProgressEvent(), progressListener ); // Execute filter this->InvokeEvent( itk::StartEvent() ); // Make sure that only the mask region is considered (otherwise, if the mask region is smaller // than the image region, the Update() would result in an exception). labelStatisticsFilter->GetOutput()->SetRequestedRegion( adaptedMaskImage->GetLargestPossibleRegion() ); // Execute the filter labelStatisticsFilter->Update(); this->InvokeEvent( itk::EndEvent() ); labelStatisticsFilter->RemoveObserver( observerTag ); // Find all relevant labels of mask (other than 0) std::list< int > relevantLabels; bool maskNonEmpty = false; unsigned int i; for ( i = 1; i < 4096; ++i ) { if ( labelStatisticsFilter->HasLabel( i ) ) { relevantLabels.push_back( i ); maskNonEmpty = true; } } if ( maskNonEmpty ) { std::list< int >::iterator it; for ( it = relevantLabels.begin(), i = 0; it != relevantLabels.end(); ++it, ++i ) { histogramContainer->push_back( HistogramType::ConstPointer( labelStatisticsFilter->GetHistogram( (*it) ) ) ); Statistics statistics; statistics.Label = (*it); statistics.N = labelStatisticsFilter->GetCount( *it ); statistics.Min = labelStatisticsFilter->GetMinimum( *it ); statistics.Max = labelStatisticsFilter->GetMaximum( *it ); statistics.Mean = labelStatisticsFilter->GetMean( *it ); statistics.Median = labelStatisticsFilter->GetMedian( *it ); statistics.Sigma = labelStatisticsFilter->GetSigma( *it ); statistics.RMS = sqrt( statistics.Mean * statistics.Mean + statistics.Sigma * statistics.Sigma ); // restrict image to mask area for min/max index calculation typedef itk::MaskImageFilter< ImageType, MaskImageType, ImageType > MaskImageFilterType; typename MaskImageFilterType::Pointer masker = MaskImageFilterType::New(); masker->SetOutsideValue( (statistics.Min+statistics.Max)/2 ); masker->SetInput1(adaptedImage); masker->SetInput2(adaptedMaskImage); masker->Update(); // get index of minimum and maximum typedef itk::MinimumMaximumImageCalculator< ImageType > MinMaxFilterType; typename MinMaxFilterType::Pointer minMaxFilter = MinMaxFilterType::New(); minMaxFilter->SetImage( masker->GetOutput() ); unsigned long observerTag2 = minMaxFilter->AddObserver( itk::ProgressEvent(), progressListener ); minMaxFilter->Compute(); minMaxFilter->RemoveObserver( observerTag2 ); this->InvokeEvent( itk::EndEvent() ); statistics.MinIndex.set_size(adaptedImage->GetImageDimension()); statistics.MaxIndex.set_size(adaptedImage->GetImageDimension()); typename MinMaxFilterType::IndexType tempMaxIndex = minMaxFilter->GetIndexOfMaximum(); typename MinMaxFilterType::IndexType tempMinIndex = minMaxFilter->GetIndexOfMinimum(); // FIX BUG 14644 //If a PlanarFigure is used for segmentation the //adaptedImage is a single slice (2D). Adding the // 3. dimension. if (m_MaskingMode == MASKING_MODE_PLANARFIGURE && m_Image->GetDimension()==3) { statistics.MaxIndex.set_size(m_Image->GetDimension()); statistics.MaxIndex[m_PlanarFigureCoordinate0]=tempMaxIndex[0]; statistics.MaxIndex[m_PlanarFigureCoordinate1]=tempMaxIndex[1]; statistics.MaxIndex[m_PlanarFigureAxis]=m_PlanarFigureSlice; statistics.MinIndex.set_size(m_Image->GetDimension()); statistics.MinIndex[m_PlanarFigureCoordinate0]=tempMinIndex[0]; statistics.MinIndex[m_PlanarFigureCoordinate1]=tempMinIndex[1]; statistics.MinIndex[m_PlanarFigureAxis]=m_PlanarFigureSlice; } else { for (int i = 0; iSetRegions(region); - testImage->SetOrigin(origin); - testImage->Allocate(); - - typedef itk::ImageRegionIterator IteratorType; - IteratorType it(testImage, region); - - - double setValueBegin = 1.00; - - unsigned int lastZ = 1000000000; - unsigned int lastY = 1000000000; - for(it.GoToBegin();!it.IsAtEnd();++it) - { - if(setValueBegin <= 1000) { - - it.Set(setValueBegin ); - double value = it.Get(); - if (it.GetIndex()[1] != lastY) - { - std::cout << std::endl; - lastY = it.GetIndex()[1]; - } - if (it.GetIndex()[0] != lastZ) - { - std::cout << value << " "; - lastZ = it.GetIndex()[0]; - } - setValueBegin++; - } else { - setValueBegin = 1.00; - } - } - std::cout << std::endl << std::endl;*/ - Statistics hotspotStatistics = CalculateHotspotStatistics(adaptedImage.GetPointer(), adaptedMaskImage.GetPointer(),10.0); statistics.HotspotMean = hotspotStatistics.HotspotMean; statistics.HotspotMax = hotspotStatistics.HotspotMax; statistics.HotspotMin = hotspotStatistics.HotspotMin; + statistics.HotspotPeak = hotspotStatistics.HotspotPeak; statistics.HotspotMaxIndex = hotspotStatistics.HotspotMaxIndex; statistics.HotspotMinIndex = hotspotStatistics.HotspotMinIndex; + statistics.HotspotPeakIndex = hotspotStatistics.HotspotPeakIndex; + statistics.HotspotSigma = hotspotStatistics.HotspotSigma; statisticsContainer->push_back( statistics ); } } else { histogramContainer->push_back( HistogramType::ConstPointer( m_EmptyHistogram ) ); statisticsContainer->push_back( Statistics() ); } } template < typename TPixel, unsigned int VImageDimension> ImageStatisticsCalculator::Statistics ImageStatisticsCalculator::CalculateMinMaxIndex( const itk::Image *inputImage, itk::Image *maskImage) { // TODO: check if inputImage and maskImage have same dimensions typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::Image< unsigned short, VImageDimension > MaskImageType; typedef itk::ImageRegionConstIterator MaskImageIteratorType; typedef itk::ImageRegionConstIteratorWithIndex InputImageIndexIteratorType; StatisticsContainer statisticsContainer; MaskImageIteratorType maskIt(maskImage, maskImage->GetLargestPossibleRegion()); InputImageIndexIteratorType imageIndexIt(inputImage, inputImage->GetLargestPossibleRegion()); float maxValue = 1; float minValue = 10000; ImageType::IndexType maxIndex; // TODO: initialize ImageType::IndexType minIndex; - double sumPixelValue = 0.0; - double countPixel = 0.0; + double sumPixelValue = 0.00; + double countPixel = 0.00; for(maskIt.GoToBegin(), imageIndexIt.GoToBegin(); !maskIt.IsAtEnd() && !imageIndexIt.IsAtEnd(); ++maskIt, ++imageIndexIt) { if(maskIt.Get() > itk::NumericTraits::Zero) // TODO: was ist der Unterschied zwischen itk::NumericTraits::Zero und "0" { - //Calculate coefficients for Mean-Value + //Calculate coefficients for Mean-Value / StdDev sumPixelValue = sumPixelValue + imageIndexIt.Get(); countPixel++; - //Calculate Min and Max and corresponding Index-Values + //Calculate minimum, maximum and corresponding index-values if(imageIndexIt.Get() > maxValue) { maxIndex = imageIndexIt.GetIndex(); maxValue = imageIndexIt.Get(); } if(imageIndexIt.Get() < minValue) { minIndex = imageIndexIt.GetIndex(); minValue = imageIndexIt.Get(); } } } - Statistics stats; - stats.HotspotMinIndex.set_size(inputImage->GetImageDimension()); - stats.HotspotMaxIndex.set_size(inputImage->GetImageDimension()); + double mean = sumPixelValue / countPixel; + double stdDevNumerator = 0.00; + + //Calculation Numerator StdDev + for(maskIt.GoToBegin(), imageIndexIt.GoToBegin(); + !maskIt.IsAtEnd() && !imageIndexIt.IsAtEnd(); + ++maskIt, ++imageIndexIt) + { + if(maskIt.Get() > itk::NumericTraits::Zero) + { + stdDevNumerator += pow((imageIndexIt.Get() - mean), 2.00); + } + } + + Statistics statistics; + statistics.HotspotSigma = sqrt(stdDevNumerator / countPixel); + statistics.HotspotMinIndex.set_size(inputImage->GetImageDimension()); + statistics.HotspotMaxIndex.set_size(inputImage->GetImageDimension()); - for (int i = 0; i ImageStatisticsCalculator::Statistics ImageStatisticsCalculator::CalculateHotspotStatistics( const itk::Image *inputImage, itk::Image *maskImage, double RadiusInMM) { typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::Image< float, VImageDimension > MaskImageType; + typedef itk::Image SphereMaskImageType; typedef itk::ContinuousIndex ContinuousIndexType; typedef itk::ImageRegionConstIteratorWithIndex IteratorType; typedef itk::ImageRegionConstIteratorWithIndex MaskIteratorType; + typedef itk::ImageRegionIteratorWithIndex SphereMaskIteratorType; typedef typename ImageType::SpacingType SpacingType; typedef typename ImageType::SizeType SizeType; typedef typename ImageType::IndexType IndexType; typedef typename ImageType::PointType PointType; typedef typename ImageType::RegionType RegionType; MaskImageType::Pointer convolutionMask = MaskImageType::New(); SpacingType spacing = inputImage->GetSpacing(); IndexType start; start.Fill(0); ContinuousIndexType origin; SizeType size; ContinuousIndexType convolutionMaskCenterCoordinate; for(unsigned int i = 0; i < VImageDimension; ++i) { origin[i] = 0.0; double countIndex = 2.0 * RadiusInMM / spacing[i]; //Rounding up to the next integer by cast countIndex += 0.9; int castedIndex = static_cast(countIndex); //We always have an uneven number in size to determine a center-point in the convolution mask if(castedIndex % 2 > 0 ) { size[i] = castedIndex; } else { size[i] = castedIndex +1; } convolutionMaskCenterCoordinate[i] = (size[i] -1) / 2; } RegionType region; region.SetSize(size); region.SetIndex(start); convolutionMask->SetRegions(region); - convolutionMask->SetOrigin(origin); convolutionMask->SetSpacing(spacing); convolutionMask->Allocate(); float subPixelDimensionX = spacing[0]/2; float subPixelDimensionY = spacing[1]/2; - double amountOfPixels = size[0] * size[1]; double distance = 0.0; - int countSubPixel = 0; + double countSubPixel = 0.0; double pixelValue = 0.0; MaskIteratorType maskIt(convolutionMask,region); - - - ////#ifdef DEBUG_SEGMENTATION_CORRECTION - // unsigned int lastZ = 1000000000; - // unsigned int lastY = 1000000000; - ////#endif for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt) { ContinuousIndexType indexPoint(maskIt.GetIndex()); for(double x = indexPoint[0] - subPixelDimensionX / 2; x <= indexPoint[0] + subPixelDimensionX / 2; x += subPixelDimensionX) { for(double y = indexPoint[1] - subPixelDimensionY /2; y <= indexPoint[1] + subPixelDimensionY / 2; y += subPixelDimensionY) { ContinuousIndexType subPixelCenterCoordinate; subPixelCenterCoordinate[0] = x; subPixelCenterCoordinate[1] = y; for( unsigned int i = 2; i < VImageDimension; ++i ) { subPixelCenterCoordinate[i] = indexPoint[i]; } distance = subPixelCenterCoordinate.EuclideanDistanceTo(convolutionMaskCenterCoordinate); if(distance <= RadiusInMM) countSubPixel++; } } //pixelValue is the counted SubPixel divided by factor 4 pixelValue = countSubPixel / 4.00; - - convolutionMask->SetPixel(maskIt.GetIndex(),pixelValue); - ////#ifdef DEBUG_SEGMENTATION_CORRECTION - // // Debug Ausgabe: - //double value = maskIt.Get(); - // if (maskIt.GetIndex()[1] != lastY) - // { - // std::cout << std::endl; - // lastY = maskIt.GetIndex()[1]; - // } - // if (maskIt.GetIndex()[0] != lastZ) - // { - // std::cout << value << " "; - // lastZ = maskIt.GetIndex()[0]; - // } - ////#endif - - countSubPixel = 0; + countSubPixel = 0.00; } - std::cout << std::endl << std::endl; - + //Initialize Convolution-Filter typedef itk::ConvolutionImageFilter FilterType; FilterType::Pointer convolutionFilter = FilterType::New(); convolutionFilter->SetInput(inputImage); convolutionFilter->SetKernelImage(convolutionMask); convolutionFilter->SetNormalize(true); convolutionFilter->Update(); MaskImageType::Pointer peakImage = convolutionFilter->GetOutput(); MaskIteratorType peakImageIt(peakImage, peakImage->GetLargestPossibleRegion()); - //#ifdef DEBUG_SEGMENTATION_CORRECTION - // Debug Ausgabe: - unsigned int lastZ = 1000000000; - unsigned int lastY = 1000000000; - for(peakImageIt.GoToBegin(); !peakImageIt.IsAtEnd(); ++peakImageIt) - { - double x = peakImageIt.Get(); - if (peakImageIt.GetIndex()[1] != lastY) - { - std::cout << std::endl; - lastY = peakImageIt.GetIndex()[1]; - } - if (peakImageIt.GetIndex()[0] != lastZ) - { - std::cout << x << " "; - lastZ = peakImageIt.GetIndex()[0]; - } - } - //#endif + Statistics hotspotStatistics; hotspotStatistics = CalculateMinMaxIndex(peakImage.GetPointer(),maskImage); + + //Save Peak-Value (Peak-Value is MaxValue in a peakImage) + double hotspotPeak = hotspotStatistics.HotspotMax; + + SphereMaskImageType::IndexType hotspotPeakIndex; + + //Save Peak-Index + hotspotStatistics.HotspotMaxIndex.set_size(inputImage->GetImageDimension()); + for (int i = 0; i < hotspotStatistics.HotspotMaxIndex.size(); i++) + { + hotspotPeakIndex[i] = hotspotStatistics.HotspotMaxIndex[i]; + } + + SphereMaskImageType::Pointer hotspotMask = SphereMaskImageType::New(); + + SpacingType hotspotSpacing = inputImage->GetSpacing(); + const double radiusSUVHotspot = 6.2035049089940; + IndexType hotspotStart; + + hotspotStart.Fill(0); + ContinuousIndexType hotspotMaskCenterIndex; + + //Set hotspotMask-origin on position of Peak-Index + hotspotStatistics.HotspotMaxIndex.set_size(inputImage->GetImageDimension()); + for (int i = 0; iGetLargestPossibleRegion().GetSize()); + hotspotRegion.SetIndex(hotspotStart); + + hotspotMask->SetRegions(hotspotRegion); + hotspotMask->SetSpacing(hotspotSpacing); + hotspotMask->Allocate(); + + SphereMaskIteratorType hotspotMaskIt(hotspotMask,hotspotRegion); + + //Calculate which pixels belong to hotspotMask + for(hotspotMaskIt.GoToBegin(); !hotspotMaskIt.IsAtEnd(); ++hotspotMaskIt) + { + ContinuousIndexType indexPoint(hotspotMaskIt.GetIndex()); + double distance = 0.0; + distance = indexPoint.EuclideanDistanceTo(hotspotMaskCenterIndex); + + if(distance <= radiusSUVHotspot) + hotspotMask->SetPixel(hotspotMaskIt.GetIndex(), 1.00); + else + hotspotMask->SetPixel(hotspotMaskIt.GetIndex(), 0.00); + } + + //Calculate statistics in Hotspot + hotspotStatistics = CalculateMinMaxIndex(inputImage, hotspotMask.GetPointer()); + hotspotStatistics.HotspotPeak = hotspotPeak; + + hotspotStatistics.HotspotPeakIndex.set_size(inputImage->GetImageDimension()); + for (int i = 0; i< hotspotStatistics.HotspotPeakIndex.size(); ++i) + { + hotspotStatistics.HotspotPeakIndex[i] = hotspotPeakIndex[i]; + } + return hotspotStatistics; } template < typename TPixel, unsigned int VImageDimension > void ImageStatisticsCalculator::InternalCalculateMaskFromPlanarFigure( const itk::Image< TPixel, VImageDimension > *image, unsigned int axis ) { typedef itk::Image< TPixel, VImageDimension > ImageType; typedef itk::CastImageFilter< ImageType, MaskImage2DType > CastFilterType; // Generate mask image as new image with same header as input image and // initialize with "1". typename CastFilterType::Pointer castFilter = CastFilterType::New(); castFilter->SetInput( image ); castFilter->Update(); castFilter->GetOutput()->FillBuffer( 1 ); // all PolylinePoints of the PlanarFigure are stored in a vtkPoints object. // These points are used by the vtkLassoStencilSource to create // a vtkImageStencil. const mitk::Geometry2D *planarFigureGeometry2D = m_PlanarFigure->GetGeometry2D(); const typename PlanarFigure::PolyLineType planarFigurePolyline = m_PlanarFigure->GetPolyLine( 0 ); const mitk::Geometry3D *imageGeometry3D = m_Image->GetGeometry( 0 ); // Determine x- and y-dimensions depending on principal axis int i0, i1; switch ( axis ) { case 0: i0 = 1; i1 = 2; break; case 1: i0 = 0; i1 = 2; break; case 2: default: i0 = 0; i1 = 1; break; } m_PlanarFigureCoordinate0= i0; m_PlanarFigureCoordinate1= i1; // store the polyline contour as vtkPoints object bool outOfBounds = false; vtkSmartPointer points = vtkSmartPointer::New(); typename PlanarFigure::PolyLineType::const_iterator it; for ( it = planarFigurePolyline.begin(); it != planarFigurePolyline.end(); ++it ) { Point3D point3D; // Convert 2D point back to the local index coordinates of the selected // image planarFigureGeometry2D->Map( it->Point, point3D ); // Polygons (partially) outside of the image bounds can not be processed // further due to a bug in vtkPolyDataToImageStencil if ( !imageGeometry3D->IsInside( point3D ) ) { outOfBounds = true; } imageGeometry3D->WorldToIndex( point3D, point3D ); points->InsertNextPoint( point3D[i0], point3D[i1], 0 ); } // mark a malformed 2D planar figure ( i.e. area = 0 ) as out of bounds // this can happen when all control points of a rectangle lie on the same line = two of the three extents are zero double bounds[6] = {0, 0, 0, 0, 0, 0}; points->GetBounds( bounds ); bool extent_x = (fabs(bounds[0] - bounds[1])) < mitk::eps; bool extent_y = (fabs(bounds[2] - bounds[3])) < mitk::eps; bool extent_z = (fabs(bounds[4] - bounds[5])) < mitk::eps; // throw an exception if a closed planar figure is deformed, i.e. has only one non-zero extent if ( m_PlanarFigure->IsClosed() && ((extent_x && extent_y) || (extent_x && extent_z) || (extent_y && extent_z))) { mitkThrow() << "Figure has a zero area and cannot be used for masking."; } if ( outOfBounds ) { throw std::runtime_error( "Figure at least partially outside of image bounds!" ); } // create a vtkLassoStencilSource and set the points of the Polygon vtkSmartPointer lassoStencil = vtkSmartPointer::New(); lassoStencil->SetShapeToPolygon(); lassoStencil->SetPoints( points ); // Export from ITK to VTK (to use a VTK filter) typedef itk::VTKImageImport< MaskImage2DType > ImageImportType; typedef itk::VTKImageExport< MaskImage2DType > ImageExportType; typename ImageExportType::Pointer itkExporter = ImageExportType::New(); itkExporter->SetInput( castFilter->GetOutput() ); vtkSmartPointer vtkImporter = vtkSmartPointer::New(); this->ConnectPipelines( itkExporter, vtkImporter ); // Apply the generated image stencil to the input image vtkSmartPointer imageStencilFilter = vtkSmartPointer::New(); imageStencilFilter->SetInputConnection( vtkImporter->GetOutputPort() ); imageStencilFilter->SetStencil( lassoStencil->GetOutput() ); imageStencilFilter->ReverseStencilOff(); imageStencilFilter->SetBackgroundValue( 0 ); imageStencilFilter->Update(); // Export from VTK back to ITK vtkSmartPointer vtkExporter = vtkImageExport::New(); // TODO: this is WRONG, should be vtkSmartPointer::New(), but bug # 14455 vtkExporter->SetInputConnection( imageStencilFilter->GetOutputPort() ); vtkExporter->Update(); typename ImageImportType::Pointer itkImporter = ImageImportType::New(); this->ConnectPipelines( vtkExporter, itkImporter ); itkImporter->Update(); // Store mask m_InternalImageMask2D = itkImporter->GetOutput(); } void ImageStatisticsCalculator::UnmaskedStatisticsProgressUpdate() { // Need to throw away every second progress event to reach a final count of // 100 since two consecutive filters are used in this case static int updateCounter = 0; if ( updateCounter++ % 2 == 0 ) { this->InvokeEvent( itk::ProgressEvent() ); } } void ImageStatisticsCalculator::MaskedStatisticsProgressUpdate() { this->InvokeEvent( itk::ProgressEvent() ); } } diff --git a/Modules/ImageStatistics/mitkImageStatisticsCalculator.h b/Modules/ImageStatistics/mitkImageStatisticsCalculator.h index c563182284..1ed0cf658d 100644 --- a/Modules/ImageStatistics/mitkImageStatisticsCalculator.h +++ b/Modules/ImageStatistics/mitkImageStatisticsCalculator.h @@ -1,366 +1,369 @@ /*=================================================================== 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. ===================================================================*/ #ifndef _MITK_IMAGESTATISTICSCALCULATOR_H #define _MITK_IMAGESTATISTICSCALCULATOR_H #include #include "ImageStatisticsExports.h" #include #include #ifndef __itkHistogram_h #include #endif #include "mitkImage.h" #include "mitkImageTimeSelector.h" #include "mitkPlanarFigure.h" #include namespace mitk { /** * \brief Class for calculating statistics and histogram for an (optionally * masked) image. * * Images can be masked by either a label image (of the same dimensions as * the original image) or by a closed mitk::PlanarFigure, e.g. a circle or * polygon. When masking with a planar figure, the slice corresponding to the * plane containing the figure is extracted and then clipped with contour * defined by the figure. Planar figures need to be aligned along the main axes * of the image (axial, sagittal, coronal). Planar figures on arbitrary * rotated planes are not supported. * * For each operating mode (no masking, masking by image, masking by planar * figure), the calculated statistics and histogram are cached so that, when * switching back and forth between operation modes without modifying mask or * image, the information doesn't need to be recalculated. * * Note: currently time-resolved and multi-channel pictures are not properly * supported. */ class ImageStatistics_EXPORT ImageStatisticsCalculator : public itk::Object { public: enum { MASKING_MODE_NONE = 0, MASKING_MODE_IMAGE, MASKING_MODE_PLANARFIGURE }; typedef itk::Statistics::Histogram HistogramType; typedef HistogramType::ConstIterator HistogramConstIteratorType; struct Statistics { int Label; unsigned int N; double Min; double Max; double Mean; double Median; double Variance; double Sigma; double RMS; double HotspotMin; double HotspotMax; double HotspotMean; - double HotspotVariance; + double HotspotSigma; + double HotspotPeak; vnl_vector< int > MinIndex; vnl_vector< int > MaxIndex; - vnl_vector HotspotMaxIndex; - vnl_vector HotspotMinIndex; + vnl_vector HotspotMaxIndex; + vnl_vector HotspotMinIndex; + vnl_vector HotspotPeakIndex; void Reset() { Label = 0; N = 0; Min = 0.0; Max = 0.0; Mean = 0.0; Median = 0.0; Variance = 0.0; Sigma = 0.0; RMS = 0.0; HotspotMin = 0.0; HotspotMax = 0.0; HotspotMean = 0.0; - HotspotVariance = 0.0; + HotspotPeak = 0.0; + HotspotSigma = 0.0; } }; typedef std::vector< HistogramType::ConstPointer > HistogramContainer; typedef std::vector< Statistics > StatisticsContainer; mitkClassMacro( ImageStatisticsCalculator, itk::Object ); itkNewMacro( ImageStatisticsCalculator ); /** \brief Set image from which to compute statistics. */ void SetImage( const mitk::Image *image ); /** \brief Set image for masking. */ void SetImageMask( const mitk::Image *imageMask ); /** \brief Set planar figure for masking. */ void SetPlanarFigure( mitk::PlanarFigure *planarFigure ); /** \brief Set/Get operation mode for masking */ void SetMaskingMode( unsigned int mode ); /** \brief Set/Get operation mode for masking */ itkGetMacro( MaskingMode, unsigned int ); /** \brief Set/Get operation mode for masking */ void SetMaskingModeToNone(); /** \brief Set/Get operation mode for masking */ void SetMaskingModeToImage(); /** \brief Set/Get operation mode for masking */ void SetMaskingModeToPlanarFigure(); /** \brief Set a pixel value for pixels that will be ignored in the statistics */ void SetIgnorePixelValue(double value); /** \brief Get the pixel value for pixels that will be ignored in the statistics */ double GetIgnorePixelValue(); /** \brief Set wether a pixel value should be ignored in the statistics */ void SetDoIgnorePixelValue(bool doit); /** \brief Get wether a pixel value will be ignored in the statistics */ bool GetDoIgnorePixelValue(); void SetHotspotSize (double hotspotRadiusInMM); double GetHotspotSize(); void SetCalculateHotspot(bool calculateHotspot); bool IsHotspotCalculated(); /** \brief Compute statistics (together with histogram) for the current * masking mode. * * Computation is not executed if statistics is already up to date. In this * case, false is returned; otherwise, true.*/ virtual bool ComputeStatistics( unsigned int timeStep = 0 ); /** \brief Retrieve the histogram depending on the current masking mode. * * \param label The label for which to retrieve the histogram in multi-label situations (ascending order). */ const HistogramType *GetHistogram( unsigned int timeStep = 0, unsigned int label = 0 ) const; /** \brief Retrieve the histogram depending on the current masking mode (for all image labels. */ const HistogramContainer &GetHistogramVector( unsigned int timeStep = 0 ) const; /** \brief Retrieve statistics depending on the current masking mode. * * \param label The label for which to retrieve the statistics in multi-label situations (ascending order). */ const Statistics &GetStatistics( unsigned int timeStep = 0, unsigned int label = 0 ) const; /** \brief Retrieve statistics depending on the current masking mode. * TODO: Kommentare anpassen! * \param label The label for which to retrieve the statistics in multi-label situations (ascending order). */ const Statistics &GetHotspotStatistics( unsigned int timeStep = 0, unsigned int label = 0 ) const; /** \brief Retrieve statistics depending on the current masking mode (for all image labels). */ const StatisticsContainer &GetStatisticsVector( unsigned int timeStep = 0 ) const; protected: typedef std::vector< HistogramContainer > HistogramVector; typedef std::vector< StatisticsContainer > StatisticsVector; typedef std::vector< itk::TimeStamp > TimeStampVectorType; typedef std::vector< bool > BoolVectorType; typedef itk::Image< unsigned short, 3 > MaskImage3DType; typedef itk::Image< unsigned short, 2 > MaskImage2DType; ImageStatisticsCalculator(); virtual ~ImageStatisticsCalculator(); /** \brief Depending on the masking mode, the image and mask from which to * calculate statistics is extracted from the original input image and mask * data. * * For example, a when using a PlanarFigure as mask, the 2D image slice * corresponding to the PlanarFigure will be extracted from the original * image. If masking is disabled, the original image is simply passed * through. */ void ExtractImageAndMask( unsigned int timeStep = 0 ); /** \brief If the passed vector matches any of the three principal axes * of the passed geometry, the ínteger value corresponding to the axis * is set and true is returned. */ bool GetPrincipalAxis( const Geometry3D *geometry, Vector3D vector, unsigned int &axis ); template < typename TPixel, unsigned int VImageDimension > void InternalCalculateStatisticsUnmasked( const itk::Image< TPixel, VImageDimension > *image, StatisticsContainer* statisticsContainer, HistogramContainer *histogramContainer ); template < typename TPixel, unsigned int VImageDimension > void InternalCalculateStatisticsMasked( const itk::Image< TPixel, VImageDimension > *image, itk::Image< unsigned short, VImageDimension > *maskImage, StatisticsContainer* statisticsContainer, HistogramContainer* histogramContainer ); template < typename TPixel, unsigned int VImageDimension > void InternalCalculateMaskFromPlanarFigure( const itk::Image< TPixel, VImageDimension > *image, unsigned int axis ); template < typename TPixel, unsigned int VImageDimension > void InternalMaskIgnoredPixels( const itk::Image< TPixel, VImageDimension > *image, itk::Image< unsigned short, VImageDimension > *maskImage ); template < typename TPixel, unsigned int VImageDimension> Statistics CalculateMinMaxIndex( const itk::Image *inputImage, itk::Image *maskImage); template < typename TPixel, unsigned int VImageDimension> Statistics CalculateHotspotStatistics( const itk::Image *inputImage, itk::Image *maskImage, double RadiusInMM); /** Connection from ITK to VTK */ template void ConnectPipelines(ITK_Exporter exporter, vtkSmartPointer importer) { importer->SetUpdateInformationCallback(exporter->GetUpdateInformationCallback()); importer->SetPipelineModifiedCallback(exporter->GetPipelineModifiedCallback()); importer->SetWholeExtentCallback(exporter->GetWholeExtentCallback()); importer->SetSpacingCallback(exporter->GetSpacingCallback()); importer->SetOriginCallback(exporter->GetOriginCallback()); importer->SetScalarTypeCallback(exporter->GetScalarTypeCallback()); importer->SetNumberOfComponentsCallback(exporter->GetNumberOfComponentsCallback()); importer->SetPropagateUpdateExtentCallback(exporter->GetPropagateUpdateExtentCallback()); importer->SetUpdateDataCallback(exporter->GetUpdateDataCallback()); importer->SetDataExtentCallback(exporter->GetDataExtentCallback()); importer->SetBufferPointerCallback(exporter->GetBufferPointerCallback()); importer->SetCallbackUserData(exporter->GetCallbackUserData()); } /** Connection from VTK to ITK */ template void ConnectPipelines(vtkSmartPointer exporter, ITK_Importer importer) { importer->SetUpdateInformationCallback(exporter->GetUpdateInformationCallback()); importer->SetPipelineModifiedCallback(exporter->GetPipelineModifiedCallback()); importer->SetWholeExtentCallback(exporter->GetWholeExtentCallback()); importer->SetSpacingCallback(exporter->GetSpacingCallback()); importer->SetOriginCallback(exporter->GetOriginCallback()); importer->SetScalarTypeCallback(exporter->GetScalarTypeCallback()); importer->SetNumberOfComponentsCallback(exporter->GetNumberOfComponentsCallback()); importer->SetPropagateUpdateExtentCallback(exporter->GetPropagateUpdateExtentCallback()); importer->SetUpdateDataCallback(exporter->GetUpdateDataCallback()); importer->SetDataExtentCallback(exporter->GetDataExtentCallback()); importer->SetBufferPointerCallback(exporter->GetBufferPointerCallback()); importer->SetCallbackUserData(exporter->GetCallbackUserData()); } void UnmaskedStatisticsProgressUpdate(); void MaskedStatisticsProgressUpdate(); /** m_Image contains the input image (e.g. 2D, 3D, 3D+t)*/ mitk::Image::ConstPointer m_Image; mitk::Image::ConstPointer m_ImageMask; mitk::PlanarFigure::Pointer m_PlanarFigure; HistogramVector m_ImageHistogramVector; HistogramVector m_MaskedImageHistogramVector; HistogramVector m_PlanarFigureHistogramVector; HistogramType::Pointer m_EmptyHistogram; HistogramContainer m_EmptyHistogramContainer; StatisticsVector m_ImageStatisticsVector; StatisticsVector m_MaskedImageStatisticsVector; StatisticsVector m_PlanarFigureStatisticsVector; StatisticsVector m_MaskedImageHotspotStatisticsVector; Statistics m_EmptyStatistics; StatisticsContainer m_EmptyStatisticsContainer; unsigned int m_MaskingMode; bool m_MaskingModeChanged; /** m_InternalImage contains a image volume at one time step (e.g. 2D, 3D)*/ mitk::Image::ConstPointer m_InternalImage; MaskImage3DType::Pointer m_InternalImageMask3D; MaskImage2DType::Pointer m_InternalImageMask2D; TimeStampVectorType m_ImageStatisticsTimeStampVector; TimeStampVectorType m_MaskedImageStatisticsTimeStampVector; TimeStampVectorType m_PlanarFigureStatisticsTimeStampVector; BoolVectorType m_ImageStatisticsCalculationTriggerVector; BoolVectorType m_MaskedImageStatisticsCalculationTriggerVector; BoolVectorType m_PlanarFigureStatisticsCalculationTriggerVector; double m_IgnorePixelValue; bool m_DoIgnorePixelValue; bool m_IgnorePixelValueChanged; double m_HotspotSize; bool m_CalculateHotspot; unsigned int m_PlanarFigureAxis; // Normal axis for PlanarFigure unsigned int m_PlanarFigureSlice; // Slice which contains PlanarFigure int m_PlanarFigureCoordinate0; // First plane-axis for PlanarFigure int m_PlanarFigureCoordinate1; // Second plane-axis for PlanarFigure }; } #endif // #define _MITK_IMAGESTATISTICSCALCULATOR_H 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 af76e6b94e..6d14fc75a0 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsView.cpp @@ -1,733 +1,749 @@ /*=================================================================== 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 "QmitkImageStatisticsView.h" // Qt includes #include // berry includes #include // mitk includes #include "mitkNodePredicateDataType.h" #include "mitkPlanarFigureInteractor.h" // itk includes #include "itksys/SystemTools.hxx" #include #include const std::string QmitkImageStatisticsView::VIEW_ID = "org.mitk.views.imagestatistics"; QmitkImageStatisticsView::QmitkImageStatisticsView(QObject* /*parent*/, const char* /*name*/) : m_Controls( NULL ), m_TimeStepperAdapter( NULL ), m_SelectedImage( NULL ), m_SelectedImageMask( NULL ), m_SelectedPlanarFigure( NULL ), m_ImageObserverTag( -1 ), m_ImageMaskObserverTag( -1 ), m_PlanarFigureObserverTag( -1 ), m_CurrentStatisticsValid( false ), m_StatisticsUpdatePending( false ), m_DataNodeSelectionChanged ( false ), m_Visible(false) { this->m_CalculationThread = new QmitkImageStatisticsCalculationThread; } QmitkImageStatisticsView::~QmitkImageStatisticsView() { if ( m_SelectedImage != NULL ) m_SelectedImage->RemoveObserver( m_ImageObserverTag ); if ( m_SelectedImageMask != NULL ) m_SelectedImageMask->RemoveObserver( m_ImageMaskObserverTag ); if ( m_SelectedPlanarFigure != NULL ) m_SelectedPlanarFigure->RemoveObserver( m_PlanarFigureObserverTag ); while(this->m_CalculationThread->isRunning()) // wait until thread has finished { itksys::SystemTools::Delay(100); } delete this->m_CalculationThread; } void QmitkImageStatisticsView::CreateQtPartControl(QWidget *parent) { if (m_Controls == NULL) { m_Controls = new Ui::QmitkImageStatisticsViewControls; m_Controls->setupUi(parent); this->CreateConnections(); m_Controls->m_ErrorMessageLabel->hide(); m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); m_Controls->m_LineProfileWidget->SetPathModeToPlanarFigure(); } } void QmitkImageStatisticsView::CreateConnections() { if ( m_Controls ) { connect( (QObject*)(this->m_Controls->m_ButtonCopyHistogramToClipboard), SIGNAL(clicked()),(QObject*) this, SLOT(OnClipboardHistogramButtonClicked()) ); connect( (QObject*)(this->m_Controls->m_ButtonCopyStatisticsToClipboard), SIGNAL(clicked()),(QObject*) this, SLOT(OnClipboardStatisticsButtonClicked()) ); connect( (QObject*)(this->m_Controls->m_IgnoreZerosCheckbox), SIGNAL(clicked()),(QObject*) this, SLOT(OnIgnoreZerosCheckboxClicked()) ); connect( (QObject*) this->m_CalculationThread, SIGNAL(finished()),this, SLOT( OnThreadedStatisticsCalculationEnds()),Qt::QueuedConnection); connect( (QObject*) this, SIGNAL(StatisticsUpdate()),this, SLOT( RequestStatisticsUpdate()), Qt::QueuedConnection); connect( (QObject*) this->m_Controls->m_StatisticsTable, SIGNAL(cellDoubleClicked(int,int)),this, SLOT( JumpToCoordinates(int,int)) ); connect( (QObject*) (this->m_Controls->m_barRadioButton), SIGNAL(clicked()), (QObject*) (this->m_Controls->m_JSHistogram), SLOT(OnBarRadioButtonSelected())); connect( (QObject*) (this->m_Controls->m_lineRadioButton), SIGNAL(clicked()), (QObject*) (this->m_Controls->m_JSHistogram), SLOT(OnLineRadioButtonSelected())); } } void QmitkImageStatisticsView::JumpToCoordinates(int row ,int col) { mitk::Point3D world; if (row==4) world = m_WorldMin; else if (row==3) world = m_WorldMax; else return; mitk::IRenderWindowPart* part = this->GetRenderWindowPart(); if (part) { part->GetQmitkRenderWindow("axial")->GetSliceNavigationController()->SelectSliceByPoint(world); part->GetQmitkRenderWindow("sagittal")->GetSliceNavigationController()->SelectSliceByPoint(world); part->GetQmitkRenderWindow("coronal")->GetSliceNavigationController()->SelectSliceByPoint(world); } } void QmitkImageStatisticsView::OnIgnoreZerosCheckboxClicked() { emit StatisticsUpdate(); } void QmitkImageStatisticsView::OnClipboardHistogramButtonClicked() { if ( m_CurrentStatisticsValid ) { typedef mitk::ImageStatisticsCalculator::HistogramType HistogramType; const HistogramType *histogram = this->m_CalculationThread->GetTimeStepHistogram().GetPointer(); QString clipboard( "Measurement \t Frequency\n" ); for ( HistogramType::ConstIterator it = histogram->Begin(); it != histogram->End(); ++it ) { clipboard = clipboard.append( "%L1 \t %L2\n" ) .arg( it.GetMeasurementVector()[0], 0, 'f', 2 ) .arg( it.GetFrequency() ); } QApplication::clipboard()->setText( clipboard, QClipboard::Clipboard ); } else { QApplication::clipboard()->clear(); } } void QmitkImageStatisticsView::OnClipboardStatisticsButtonClicked() { if ( this->m_CurrentStatisticsValid ) { const mitk::ImageStatisticsCalculator::Statistics &statistics = this->m_CalculationThread->GetStatisticsData(); // Copy statistics to clipboard ("%Ln" will use the default locale for // number formatting) QString clipboard( "Mean \t StdDev \t RMS \t Max \t Min \t N \t V (mm³)\n" ); clipboard = clipboard.append( "%L1 \t %L2 \t %L3 \t %L4 \t %L5 \t %L6 \t %L7" ) .arg( statistics.Mean, 0, 'f', 10 ) .arg( statistics.Sigma, 0, 'f', 10 ) .arg( statistics.RMS, 0, 'f', 10 ) .arg( statistics.Max, 0, 'f', 10 ) .arg( statistics.Min, 0, 'f', 10 ) .arg( statistics.N ) .arg( m_Controls->m_StatisticsTable->item( 0, 6 )->text() ); QApplication::clipboard()->setText( clipboard, QClipboard::Clipboard ); } else { QApplication::clipboard()->clear(); } } void QmitkImageStatisticsView::OnSelectionChanged( berry::IWorkbenchPart::Pointer /*part*/, const QList &selectedNodes ) { if (this->m_Visible) { this->SelectionChanged( selectedNodes ); } else { this->m_DataNodeSelectionChanged = true; } } void QmitkImageStatisticsView::SelectionChanged(const QList &selectedNodes) { if( this->m_StatisticsUpdatePending ) { this->m_DataNodeSelectionChanged = true; return; // not ready for new data now! } if (selectedNodes.size() == this->m_SelectedDataNodes.size()) { int i = 0; for (; i < selectedNodes.size(); ++i) { if (selectedNodes.at(i) != this->m_SelectedDataNodes.at(i)) { break; } } // node selection did not change if (i == selectedNodes.size()) return; } this->ReinitData(); if (!selectedNodes.size()) { m_Controls->m_JSHistogram->ClearHistogram(); m_Controls->m_lineRadioButton->setEnabled(true); m_Controls->m_barRadioButton->setEnabled(true); m_Controls->m_InfoLabel->setText(QString("")); } if(selectedNodes.size() == 1 || selectedNodes.size() == 2) { bool isBinary = false; selectedNodes.value(0)->GetBoolProperty("binary",isBinary); if(isBinary) { m_Controls->m_JSHistogram->ClearHistogram(); m_Controls->m_lineRadioButton->setEnabled(true); m_Controls->m_barRadioButton->setEnabled(true); m_Controls->m_InfoLabel->setText(QString("")); } for (int i= 0; i< selectedNodes.size(); ++i) { this->m_SelectedDataNodes.push_back(selectedNodes.at(i)); } this->m_DataNodeSelectionChanged = false; this->m_Controls->m_ErrorMessageLabel->setText( "" ); this->m_Controls->m_ErrorMessageLabel->hide(); emit StatisticsUpdate(); } else { this->m_DataNodeSelectionChanged = false; } } void QmitkImageStatisticsView::ReinitData() { while( this->m_CalculationThread->isRunning()) // wait until thread has finished { itksys::SystemTools::Delay(100); } if(this->m_SelectedImage != NULL) { this->m_SelectedImage->RemoveObserver( this->m_ImageObserverTag); this->m_SelectedImage = NULL; } if(this->m_SelectedImageMask != NULL) { this->m_SelectedImageMask->RemoveObserver( this->m_ImageMaskObserverTag); this->m_SelectedImageMask = NULL; } if(this->m_SelectedPlanarFigure != NULL) { this->m_SelectedPlanarFigure->RemoveObserver( this->m_PlanarFigureObserverTag); this->m_SelectedPlanarFigure = NULL; } this->m_SelectedDataNodes.clear(); this->m_StatisticsUpdatePending = false; m_Controls->m_ErrorMessageLabel->setText( "" ); m_Controls->m_ErrorMessageLabel->hide(); this->InvalidateStatisticsTableView(); m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); } void QmitkImageStatisticsView::OnThreadedStatisticsCalculationEnds() { std::stringstream message; message << ""; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->hide(); this->WriteStatisticsToGUI(); } void QmitkImageStatisticsView::UpdateStatistics() { mitk::IRenderWindowPart* renderPart = this->GetRenderWindowPart(); if ( renderPart == NULL ) { this->m_StatisticsUpdatePending = false; return; } m_WorldMin.Fill(-1); m_WorldMax.Fill(-1); // classify selected nodes mitk::NodePredicateDataType::Pointer imagePredicate = mitk::NodePredicateDataType::New("Image"); std::string maskName = std::string(); std::string maskType = std::string(); unsigned int maskDimension = 0; // reset data from last run ITKCommandType::Pointer changeListener = ITKCommandType::New(); changeListener->SetCallbackFunction( this, &QmitkImageStatisticsView::SelectedDataModified ); mitk::DataNode::Pointer planarFigureNode; for( int i= 0 ; i < this->m_SelectedDataNodes.size(); ++i) { mitk::PlanarFigure::Pointer planarFig = dynamic_cast(this->m_SelectedDataNodes.at(i)->GetData()); if( imagePredicate->CheckNode(this->m_SelectedDataNodes.at(i)) ) { bool isMask = false; this->m_SelectedDataNodes.at(i)->GetPropertyValue("binary", isMask); if( this->m_SelectedImageMask == NULL && isMask) { this->m_SelectedImageMask = dynamic_cast(this->m_SelectedDataNodes.at(i)->GetData()); this->m_ImageMaskObserverTag = this->m_SelectedImageMask->AddObserver(itk::ModifiedEvent(), changeListener); maskName = this->m_SelectedDataNodes.at(i)->GetName(); maskType = m_SelectedImageMask->GetNameOfClass(); maskDimension = 3; } else if( !isMask ) { if(this->m_SelectedImage == NULL) { this->m_SelectedImage = static_cast(this->m_SelectedDataNodes.at(i)->GetData()); this->m_ImageObserverTag = this->m_SelectedImage->AddObserver(itk::ModifiedEvent(), changeListener); } } } else if (planarFig.IsNotNull()) { if(this->m_SelectedPlanarFigure == NULL) { this->m_SelectedPlanarFigure = planarFig; this->m_PlanarFigureObserverTag = this->m_SelectedPlanarFigure->AddObserver(mitk::EndInteractionPlanarFigureEvent(), changeListener); maskName = this->m_SelectedDataNodes.at(i)->GetName(); maskType = this->m_SelectedPlanarFigure->GetNameOfClass(); maskDimension = 2; planarFigureNode = m_SelectedDataNodes.at(i); } } else { std::stringstream message; message << "" << "Invalid data node type!" << ""; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); } } if(maskName == "") { maskName = "None"; maskType = ""; maskDimension = 0; } if (m_SelectedPlanarFigure != NULL && m_SelectedImage == NULL) { mitk::DataStorage::SetOfObjects::ConstPointer parentSet = this->GetDataStorage()->GetSources(planarFigureNode); for (int i=0; iSize(); i++) { mitk::DataNode::Pointer node = parentSet->ElementAt(i); if( imagePredicate->CheckNode(node) ) { bool isMask = false; node->GetPropertyValue("binary", isMask); if( !isMask ) { if(this->m_SelectedImage == NULL) { this->m_SelectedImage = static_cast(node->GetData()); this->m_ImageObserverTag = this->m_SelectedImage->AddObserver(itk::ModifiedEvent(), changeListener); } } } } } unsigned int timeStep = renderPart->GetTimeNavigationController()->GetTime()->GetPos(); if ( m_SelectedImage != NULL && m_SelectedImage->IsInitialized()) { // Check if a the selected image is a multi-channel image. If yes, statistics // cannot be calculated currently. if ( m_SelectedImage->GetPixelType().GetNumberOfComponents() > 1 ) { std::stringstream message; message << "Multi-component images not supported."; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); this->InvalidateStatisticsTableView(); m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); m_Controls->m_JSHistogram->ClearHistogram(); m_CurrentStatisticsValid = false; this->m_StatisticsUpdatePending = false; m_Controls->m_lineRadioButton->setEnabled(true); m_Controls->m_barRadioButton->setEnabled(true); m_Controls->m_InfoLabel->setText(QString("")); return; } std::stringstream maskLabel; maskLabel << maskName; if ( maskDimension > 0 ) { maskLabel << " [" << maskDimension << "D " << maskType << "]"; } m_Controls->m_SelectedMaskLabel->setText( maskLabel.str().c_str() ); // check time step validity if(m_SelectedImage->GetDimension() <= 3 && timeStep > m_SelectedImage->GetDimension(3)-1) { timeStep = m_SelectedImage->GetDimension(3)-1; } //// initialize thread and trigger it this->m_CalculationThread->SetIgnoreZeroValueVoxel( m_Controls->m_IgnoreZerosCheckbox->isChecked() ); this->m_CalculationThread->Initialize( m_SelectedImage, m_SelectedImageMask, m_SelectedPlanarFigure ); this->m_CalculationThread->SetTimeStep( timeStep ); std::stringstream message; message << "Calculating statistics..."; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); try { // Compute statistics this->m_CalculationThread->start(); } catch ( const mitk::Exception& e) { std::stringstream message; message << "" << e.GetDescription() << ""; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); this->m_StatisticsUpdatePending = false; } catch ( const std::runtime_error &e ) { // In case of exception, print error message on GUI std::stringstream message; message << "" << e.what() << ""; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); this->m_StatisticsUpdatePending = false; } catch ( const std::exception &e ) { MITK_ERROR << "Caught exception: " << e.what(); // In case of exception, print error message on GUI std::stringstream message; message << "Error! Unequal Dimensions of Image and Segmentation. No recompute possible "; m_Controls->m_ErrorMessageLabel->setText( message.str().c_str() ); m_Controls->m_ErrorMessageLabel->show(); this->m_StatisticsUpdatePending = false; } } else { this->m_StatisticsUpdatePending = false; } } void QmitkImageStatisticsView::SelectedDataModified() { if( !m_StatisticsUpdatePending ) { emit StatisticsUpdate(); } } void QmitkImageStatisticsView::NodeRemoved(const mitk::DataNode *node) { while(this->m_CalculationThread->isRunning()) // wait until thread has finished { itksys::SystemTools::Delay(100); } if (node->GetData() == m_SelectedImage) { m_SelectedImage = NULL; } } void QmitkImageStatisticsView::RequestStatisticsUpdate() { if ( !m_StatisticsUpdatePending ) { if(this->m_DataNodeSelectionChanged) { this->SelectionChanged(this->GetCurrentSelection()); } else { this->m_StatisticsUpdatePending = true; this->UpdateStatistics(); } } if (this->GetRenderWindowPart()) this->GetRenderWindowPart()->RequestUpdate(); } void QmitkImageStatisticsView::WriteStatisticsToGUI() { m_Controls->m_lineRadioButton->setEnabled(true); m_Controls->m_barRadioButton->setEnabled(true); m_Controls->m_InfoLabel->setText(QString("")); if(m_DataNodeSelectionChanged) { this->m_StatisticsUpdatePending = false; this->RequestStatisticsUpdate(); return; // stop visualization of results and calculate statistics of new selection } if ( this->m_CalculationThread->GetStatisticsUpdateSuccessFlag()) { if ( this->m_CalculationThread->GetStatisticsChangedFlag() ) { // Do not show any error messages m_Controls->m_ErrorMessageLabel->hide(); m_CurrentStatisticsValid = true; } if (m_Controls->m_barRadioButton->isChecked()) { m_Controls->m_JSHistogram->OnBarRadioButtonSelected(); } m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); m_Controls->m_JSHistogram->ComputeHistogram( this->m_CalculationThread->GetTimeStepHistogram().GetPointer() ); this->FillStatisticsTableView( this->m_CalculationThread->GetStatisticsData(), this->m_CalculationThread->GetStatisticsImage()); } else { m_Controls->m_SelectedMaskLabel->setText( "None" ); m_Controls->m_ErrorMessageLabel->setText( m_CalculationThread->GetLastErrorMessage().c_str() ); m_Controls->m_ErrorMessageLabel->show(); // Clear statistics and histogram this->InvalidateStatisticsTableView(); m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); //m_Controls->m_JSHistogram->clearHistogram(); m_CurrentStatisticsValid = false; // If a (non-closed) PlanarFigure is selected, display a line profile widget if ( m_SelectedPlanarFigure != NULL ) { // check whether PlanarFigure is initialized const mitk::Geometry2D *planarFigureGeometry2D = m_SelectedPlanarFigure->GetGeometry2D(); if ( planarFigureGeometry2D == NULL ) { // Clear statistics, histogram, and GUI this->InvalidateStatisticsTableView(); m_Controls->m_StatisticsWidgetStack->setCurrentIndex( 0 ); m_Controls->m_JSHistogram->ClearHistogram(); m_CurrentStatisticsValid = false; m_Controls->m_ErrorMessageLabel->hide(); m_Controls->m_SelectedMaskLabel->setText( "None" ); this->m_StatisticsUpdatePending = false; m_Controls->m_lineRadioButton->setEnabled(true); m_Controls->m_barRadioButton->setEnabled(true); m_Controls->m_InfoLabel->setText(QString("")); return; } unsigned int timeStep = this->GetRenderWindowPart()->GetTimeNavigationController()->GetTime()->GetPos(); m_Controls->m_JSHistogram->SetImage(this->m_CalculationThread->GetStatisticsImage()); m_Controls->m_JSHistogram->SetPlanarFigure(m_SelectedPlanarFigure); m_Controls->m_JSHistogram->ComputeIntensityProfile(timeStep); m_Controls->m_lineRadioButton->setEnabled(false); m_Controls->m_barRadioButton->setEnabled(false); std::stringstream message; message << "Only linegraph available for an intesityprofile!"; m_Controls->m_InfoLabel->setText(message.str().c_str()); } } this->m_StatisticsUpdatePending = false; } void QmitkImageStatisticsView::FillStatisticsTableView( const mitk::ImageStatisticsCalculator::Statistics &s, const mitk::Image *image ) { if (s.MaxIndex.size()==3) { mitk::Point3D index; index[0] = s.MaxIndex[0]; index[1] = s.MaxIndex[1]; index[2] = s.MaxIndex[2]; m_SelectedImage->GetGeometry()->IndexToWorld(index, m_WorldMax); index[0] = s.MinIndex[0]; index[1] = s.MinIndex[1]; index[2] = s.MinIndex[2]; m_SelectedImage->GetGeometry()->IndexToWorld(index, m_WorldMin); } int decimals = 2; mitk::PixelType doublePix = mitk::MakeScalarPixelType< double >(); mitk::PixelType floatPix = mitk::MakeScalarPixelType< float >(); if (image->GetPixelType()==doublePix || image->GetPixelType()==floatPix) decimals = 5; this->m_Controls->m_StatisticsTable->setItem( 0, 0, new QTableWidgetItem( QString("%1").arg(s.Mean, 0, 'f', decimals) ) ); this->m_Controls->m_StatisticsTable->setItem( 0, 1, new QTableWidgetItem( QString("%1").arg(s.Sigma, 0, 'f', decimals) ) ); this->m_Controls->m_StatisticsTable->setItem( 0, 2, new QTableWidgetItem( QString("%1").arg(s.RMS, 0, 'f', decimals) ) ); QString max; max.append(QString("%1").arg(s.Max, 0, 'f', decimals)); max += " ("; for (int i=0; im_Controls->m_StatisticsTable->setItem( 0, 3, new QTableWidgetItem( max ) ); QString min; min.append(QString("%1").arg(s.Min, 0, 'f', decimals)); min += " ("; for (int i=0; im_Controls->m_StatisticsTable->setItem( 0, 4, new QTableWidgetItem( min ) ); this->m_Controls->m_StatisticsTable->setItem( 0, 5, new QTableWidgetItem( QString("%1").arg(s.N) ) ); const mitk::Geometry3D *geometry = image->GetGeometry(); if ( geometry != NULL ) { const mitk::Vector3D &spacing = image->GetGeometry()->GetSpacing(); double volume = spacing[0] * spacing[1] * spacing[2] * (double) s.N; this->m_Controls->m_StatisticsTable->setItem( 0, 6, new QTableWidgetItem( QString("%1").arg(volume, 0, 'f', decimals) ) ); } else { this->m_Controls->m_StatisticsTable->setItem( 0, 6, new QTableWidgetItem( "NA" ) ); } this->m_Controls->m_StatisticsTable->setItem( 0, 7, new QTableWidgetItem( QString("%1").arg(s.HotspotMean, 0, 'f', decimals) ) ); + QString hotspotPeak; hotspotPeak.append(QString("%1").arg(s.HotspotPeak, 0, 'f', decimals)); + hotspotPeak += " ("; + for (int i=0; im_Controls->m_StatisticsTable->setItem( 0, 8, new QTableWidgetItem( hotspotPeak ) ); + + QString hotspotMax; hotspotMax.append(QString("%1").arg(s.HotspotMax, 0, 'f', decimals)); hotspotMax += " ("; for (int i=0; im_Controls->m_StatisticsTable->setItem( 0, 8, new QTableWidgetItem( hotspotMax ) ); + this->m_Controls->m_StatisticsTable->setItem( 0, 9, new QTableWidgetItem( hotspotMax ) ); QString hotspotMin; hotspotMin.append(QString("%1").arg(s.HotspotMin, 0, 'f', decimals)); hotspotMin += " ("; for (int i=0; im_Controls->m_StatisticsTable->setItem( 0, 9, new QTableWidgetItem( hotspotMin ) ); + this->m_Controls->m_StatisticsTable->setItem( 0, 10, new QTableWidgetItem( hotspotMin ) ); + + this->m_Controls->m_StatisticsTable->setItem( 0, 11, new QTableWidgetItem( + QString("%1").arg(s.HotspotSigma, 0, 'f', decimals) ) ); } void QmitkImageStatisticsView::InvalidateStatisticsTableView() { for ( unsigned int i = 0; i < 7; ++i ) { this->m_Controls->m_StatisticsTable->setItem( 0, i, new QTableWidgetItem( "NA" ) ); } } void QmitkImageStatisticsView::Activated() { } void QmitkImageStatisticsView::Deactivated() { } void QmitkImageStatisticsView::Visible() { m_Visible = true; if (m_DataNodeSelectionChanged) { if (this->IsCurrentSelectionValid()) { this->SelectionChanged(this->GetCurrentSelection()); } else { this->SelectionChanged(this->GetDataManagerSelection()); } m_DataNodeSelectionChanged = false; } } void QmitkImageStatisticsView::Hidden() { m_Visible = false; } void QmitkImageStatisticsView::SetFocus() { } diff --git a/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsViewControls.ui b/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsViewControls.ui index 7ddb5b6acf..7f890d6bb5 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsViewControls.ui +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/src/internal/QmitkImageStatisticsViewControls.ui @@ -1,480 +1,490 @@ QmitkImageStatisticsViewControls true 0 0 465 800 Form 0 0 Mask: None 2 Qt::Horizontal 40 20 color: rgb(255, 0, 0); Error Message Qt::AutoText Ignore zero-valued voxels Statistics 9 9 9 100 175 Qt::ScrollBarAlwaysOff Qt::ScrollBarAsNeeded true true true Qt::DotLine true false false 80 true 80 false true true false 25 25 false false Mean StdDev RMS Max Min N V (mm³) Hotspot Mean + + + Hotspot Peak + + Hotspot Max Hotspot Min + + + Hotspot StdDev + + Component 1 0 0 Copy to Clipboard Qt::Horizontal 40 20 150 160 Histogram false 0 0 0 0 0 0 0 Copy to Clipboard Qt::Horizontal 40 20 0 0 0 50 16777215 16777215 Plot 0 20 411 31 QLayout::SetDefaultConstraint Qt::Horizontal QSizePolicy::Preferred 10 0 0 0 Use barchart true 0 0 0 0 Use linegraph Qt::Horizontal 40 20 Qt::Vertical 20 40 QmitkVtkHistogramWidget QWidget
QmitkVtkHistogramWidget.h
1 QmitkVtkLineProfileWidget QWidget
QmitkVtkLineProfileWidget.h
1 QmitkHistogramJSWidget QWidget
QmitkHistogramJSWidget.h
1