void initialiseFilters() {
// resamplers
transform = TransformType::New();
transform->SetIdentity();
volumeInterpolator = VolumeInterpolatorType::New();
maskVolumeInterpolator = MaskVolumeInterpolatorType::New();
resampler = ResamplerType::New();
resampler->SetInput( originalImage );
resampler->SetInterpolator( volumeInterpolator );
resampler->SetOutputSpacing( resamplerSpacing );
resampler->SetSize( resamplerSize );
resampler->SetTransform( transform );
resampler->SetDefaultPixelValue( 127 );
maskResampler = MaskResamplerType::New();
maskResampler->SetInput( originalMask );
maskResampler->SetInterpolator( maskVolumeInterpolator );
maskResampler->SetOutputSpacing( resamplerSpacing );
maskResampler->SetSize( resamplerSize );
maskResampler->SetTransform( transform );
// extract image filters
sliceExtractor = SliceExtractorType::New();
sliceExtractor->SetInput( resampler->GetOutput() );
maskSliceExtractor = MaskSliceExtractorType::New();
maskSliceExtractor->SetInput( maskResampler->GetOutput() );
// masks
for(unsigned int i=0; i<resamplerSize[2]; i++) {
masks2D.push_back( MaskType2D::New() );
}
}
bool ShowSegmentationAsSmoothedSurface::ThreadedUpdateFunction()
{
Image::Pointer image;
GetPointerParameter("Input", image);
float smoothing;
GetParameter("Smoothing", smoothing);
float decimation;
GetParameter("Decimation", decimation);
float closing;
GetParameter("Closing", closing);
int timeNr = 0;
GetParameter("TimeNr", timeNr);
if (image->GetDimension() == 4)
MITK_INFO << "CREATING SMOOTHED POLYGON MODEL (t = " << timeNr << ')';
else
MITK_INFO << "CREATING SMOOTHED POLYGON MODEL";
MITK_INFO << " Smoothing = " << smoothing;
MITK_INFO << " Decimation = " << decimation;
MITK_INFO << " Closing = " << closing;
Geometry3D::Pointer geometry = dynamic_cast<Geometry3D *>(image->GetGeometry()->Clone().GetPointer());
// Make ITK image out of MITK image
typedef itk::Image<unsigned char, 3> CharImageType;
typedef itk::Image<unsigned short, 3> ShortImageType;
typedef itk::Image<float, 3> FloatImageType;
if (image->GetDimension() == 4)
{
ImageTimeSelector::Pointer imageTimeSelector = ImageTimeSelector::New();
imageTimeSelector->SetInput(image);
imageTimeSelector->SetTimeNr(timeNr);
imageTimeSelector->UpdateLargestPossibleRegion();
image = imageTimeSelector->GetOutput(0);
}
ImageToItk<CharImageType>::Pointer imageToItkFilter = ImageToItk<CharImageType>::New();
try
{
imageToItkFilter->SetInput(image);
}
catch (const itk::ExceptionObject &e)
{
// Most probably the input image type is wrong. Binary images are expected to be
// >unsigned< char images.
MITK_ERROR << e.GetDescription() << endl;
return false;
}
imageToItkFilter->Update();
CharImageType::Pointer itkImage = imageToItkFilter->GetOutput();
// Get bounding box and relabel
MITK_INFO << "Extracting VOI...";
int imageLabel = 1;
bool roiFound = false;
CharImageType::IndexType minIndex;
minIndex.Fill(numeric_limits<CharImageType::IndexValueType>::max());
CharImageType::IndexType maxIndex;
maxIndex.Fill(numeric_limits<CharImageType::IndexValueType>::min());
itk::ImageRegionIteratorWithIndex<CharImageType> iter(itkImage, itkImage->GetLargestPossibleRegion());
for (iter.GoToBegin(); !iter.IsAtEnd(); ++iter)
{
if (iter.Get() == imageLabel)
{
roiFound = true;
iter.Set(1);
CharImageType::IndexType currentIndex = iter.GetIndex();
for (unsigned int dim = 0; dim < 3; ++dim)
{
minIndex[dim] = min(currentIndex[dim], minIndex[dim]);
maxIndex[dim] = max(currentIndex[dim], maxIndex[dim]);
}
}
else
{
iter.Set(0);
}
}
if (!roiFound)
{
ProgressBar::GetInstance()->Progress(8);
MITK_ERROR << "Didn't found segmentation labeled with " << imageLabel << "!" << endl;
return false;
}
ProgressBar::GetInstance()->Progress(1);
// Extract and pad bounding box
typedef itk::RegionOfInterestImageFilter<CharImageType, CharImageType> ROIFilterType;
ROIFilterType::Pointer roiFilter = ROIFilterType::New();
CharImageType::RegionType region;
CharImageType::SizeType size;
for (unsigned int dim = 0; dim < 3; ++dim)
{
size[dim] = maxIndex[dim] - minIndex[dim] + 1;
}
region.SetIndex(minIndex);
region.SetSize(size);
roiFilter->SetInput(itkImage);
roiFilter->SetRegionOfInterest(region);
roiFilter->ReleaseDataFlagOn();
roiFilter->ReleaseDataBeforeUpdateFlagOn();
typedef itk::ConstantPadImageFilter<CharImageType, CharImageType> PadFilterType;
PadFilterType::Pointer padFilter = PadFilterType::New();
const PadFilterType::SizeValueType pad[3] = { 10, 10, 10 };
padFilter->SetInput(roiFilter->GetOutput());
padFilter->SetConstant(0);
padFilter->SetPadLowerBound(pad);
padFilter->SetPadUpperBound(pad);
padFilter->ReleaseDataFlagOn();
padFilter->ReleaseDataBeforeUpdateFlagOn();
padFilter->Update();
CharImageType::Pointer roiImage = padFilter->GetOutput();
roiImage->DisconnectPipeline();
roiFilter = nullptr;
padFilter = nullptr;
// Correct origin of real geometry (changed by cropping and padding)
typedef Geometry3D::TransformType TransformType;
TransformType::Pointer transform = TransformType::New();
TransformType::OutputVectorType translation;
for (unsigned int dim = 0; dim < 3; ++dim)
translation[dim] = (int)minIndex[dim] - (int)pad[dim];
transform->SetIdentity();
transform->Translate(translation);
geometry->Compose(transform, true);
ProgressBar::GetInstance()->Progress(1);
// Median
MITK_INFO << "Median...";
typedef itk::BinaryMedianImageFilter<CharImageType, CharImageType> MedianFilterType;
MedianFilterType::Pointer medianFilter = MedianFilterType::New();
CharImageType::SizeType radius = { 0 };
medianFilter->SetRadius(radius);
medianFilter->SetBackgroundValue(0);
medianFilter->SetForegroundValue(1);
medianFilter->SetInput(roiImage);
medianFilter->ReleaseDataFlagOn();
medianFilter->ReleaseDataBeforeUpdateFlagOn();
medianFilter->Update();
ProgressBar::GetInstance()->Progress(1);
// Intelligent closing
MITK_INFO << "Intelligent closing...";
unsigned int surfaceRatio = (unsigned int)((1.0f - closing) * 100.0f);
typedef itk::IntelligentBinaryClosingFilter<CharImageType, ShortImageType> ClosingFilterType;
ClosingFilterType::Pointer closingFilter = ClosingFilterType::New();
closingFilter->SetInput(medianFilter->GetOutput());
closingFilter->ReleaseDataFlagOn();
closingFilter->ReleaseDataBeforeUpdateFlagOn();
closingFilter->SetSurfaceRatio(surfaceRatio);
closingFilter->Update();
ShortImageType::Pointer closedImage = closingFilter->GetOutput();
closedImage->DisconnectPipeline();
roiImage = nullptr;
medianFilter = nullptr;
closingFilter = nullptr;
ProgressBar::GetInstance()->Progress(1);
// Gaussian blur
MITK_INFO << "Gauss...";
typedef itk::BinaryThresholdImageFilter<ShortImageType, FloatImageType> BinaryThresholdToFloatFilterType;
BinaryThresholdToFloatFilterType::Pointer binThresToFloatFilter = BinaryThresholdToFloatFilterType::New();
binThresToFloatFilter->SetInput(closedImage);
binThresToFloatFilter->SetLowerThreshold(1);
binThresToFloatFilter->SetUpperThreshold(1);
binThresToFloatFilter->SetInsideValue(100);
binThresToFloatFilter->SetOutsideValue(0);
binThresToFloatFilter->ReleaseDataFlagOn();
binThresToFloatFilter->ReleaseDataBeforeUpdateFlagOn();
typedef itk::DiscreteGaussianImageFilter<FloatImageType, FloatImageType> GaussianFilterType;
// From the following line on, IntelliSense (VS 2008) is broken. Any idea how to fix it?
GaussianFilterType::Pointer gaussFilter = GaussianFilterType::New();
gaussFilter->SetInput(binThresToFloatFilter->GetOutput());
gaussFilter->SetUseImageSpacing(true);
gaussFilter->SetVariance(smoothing);
gaussFilter->ReleaseDataFlagOn();
gaussFilter->ReleaseDataBeforeUpdateFlagOn();
typedef itk::BinaryThresholdImageFilter<FloatImageType, CharImageType> BinaryThresholdFromFloatFilterType;
BinaryThresholdFromFloatFilterType::Pointer binThresFromFloatFilter = BinaryThresholdFromFloatFilterType::New();
binThresFromFloatFilter->SetInput(gaussFilter->GetOutput());
binThresFromFloatFilter->SetLowerThreshold(50);
binThresFromFloatFilter->SetUpperThreshold(255);
binThresFromFloatFilter->SetInsideValue(1);
binThresFromFloatFilter->SetOutsideValue(0);
binThresFromFloatFilter->ReleaseDataFlagOn();
binThresFromFloatFilter->ReleaseDataBeforeUpdateFlagOn();
binThresFromFloatFilter->Update();
CharImageType::Pointer blurredImage = binThresFromFloatFilter->GetOutput();
blurredImage->DisconnectPipeline();
closedImage = nullptr;
binThresToFloatFilter = nullptr;
gaussFilter = nullptr;
ProgressBar::GetInstance()->Progress(1);
// Fill holes
MITK_INFO << "Filling cavities...";
typedef itk::ConnectedThresholdImageFilter<CharImageType, CharImageType> ConnectedThresholdFilterType;
ConnectedThresholdFilterType::Pointer connectedThresFilter = ConnectedThresholdFilterType::New();
CharImageType::IndexType corner;
corner[0] = 0;
corner[1] = 0;
corner[2] = 0;
connectedThresFilter->SetInput(blurredImage);
connectedThresFilter->SetSeed(corner);
connectedThresFilter->SetLower(0);
connectedThresFilter->SetUpper(0);
connectedThresFilter->SetReplaceValue(2);
connectedThresFilter->ReleaseDataFlagOn();
connectedThresFilter->ReleaseDataBeforeUpdateFlagOn();
typedef itk::BinaryThresholdImageFilter<CharImageType, CharImageType> BinaryThresholdFilterType;
BinaryThresholdFilterType::Pointer binThresFilter = BinaryThresholdFilterType::New();
binThresFilter->SetInput(connectedThresFilter->GetOutput());
binThresFilter->SetLowerThreshold(0);
binThresFilter->SetUpperThreshold(0);
binThresFilter->SetInsideValue(50);
binThresFilter->SetOutsideValue(0);
binThresFilter->ReleaseDataFlagOn();
binThresFilter->ReleaseDataBeforeUpdateFlagOn();
typedef itk::AddImageFilter<CharImageType, CharImageType, CharImageType> AddFilterType;
AddFilterType::Pointer addFilter = AddFilterType::New();
addFilter->SetInput1(blurredImage);
addFilter->SetInput2(binThresFilter->GetOutput());
addFilter->ReleaseDataFlagOn();
addFilter->ReleaseDataBeforeUpdateFlagOn();
addFilter->Update();
ProgressBar::GetInstance()->Progress(1);
// Surface extraction
MITK_INFO << "Surface extraction...";
Image::Pointer filteredImage = Image::New();
CastToMitkImage(addFilter->GetOutput(), filteredImage);
filteredImage->SetGeometry(geometry);
ImageToSurfaceFilter::Pointer imageToSurfaceFilter = ImageToSurfaceFilter::New();
imageToSurfaceFilter->SetInput(filteredImage);
imageToSurfaceFilter->SetThreshold(50);
imageToSurfaceFilter->SmoothOn();
imageToSurfaceFilter->SetDecimate(ImageToSurfaceFilter::NoDecimation);
m_Surface = imageToSurfaceFilter->GetOutput(0);
ProgressBar::GetInstance()->Progress(1);
// Mesh decimation
if (decimation > 0.0f && decimation < 1.0f)
{
MITK_INFO << "Quadric mesh decimation...";
vtkQuadricDecimation *quadricDecimation = vtkQuadricDecimation::New();
quadricDecimation->SetInputData(m_Surface->GetVtkPolyData());
quadricDecimation->SetTargetReduction(decimation);
quadricDecimation->AttributeErrorMetricOn();
quadricDecimation->GlobalWarningDisplayOff();
quadricDecimation->Update();
vtkCleanPolyData* cleaner = vtkCleanPolyData::New();
cleaner->SetInputConnection(quadricDecimation->GetOutputPort());
cleaner->PieceInvariantOn();
cleaner->ConvertLinesToPointsOn();
cleaner->ConvertStripsToPolysOn();
cleaner->PointMergingOn();
cleaner->Update();
m_Surface->SetVtkPolyData(cleaner->GetOutput());
}
ProgressBar::GetInstance()->Progress(1);
// Compute Normals
vtkPolyDataNormals* computeNormals = vtkPolyDataNormals::New();
computeNormals->SetInputData(m_Surface->GetVtkPolyData());
computeNormals->SetFeatureAngle(360.0f);
computeNormals->FlipNormalsOff();
computeNormals->Update();
m_Surface->SetVtkPolyData(computeNormals->GetOutput());
return true;
}
/**
* @brief 3D resample data to new grid size
*
* @param M Incoming data
* @param f Resampling factor in all 3 dimensions
* @param im Interpolation method (LINEAR|BSPLINE)
*
* @return Resampled data
*/
template<class T> static Matrix<T>
resample (const Matrix<T>& M, const Matrix<double>& f, const InterpMethod& im) {
Matrix <T> res = M;
#ifdef HAVE_INSIGHT
typedef typename itk::OrientedImage< T, 3 > InputImageType;
typedef typename itk::OrientedImage< T, 3 > OutputImageType;
typedef typename itk::IdentityTransform< double, 3 > TransformType;
typedef typename itk::LinearInterpolateImageFunction< InputImageType, double > InterpolatorType;
typedef typename itk::ResampleImageFilter< InputImageType, InputImageType > ResampleFilterType;
typename InterpolatorType::Pointer linterp = InterpolatorType::New();
TransformType::Pointer trafo = TransformType::New();
trafo->SetIdentity();
typename InputImageType::SpacingType space;
space[0] = 1.0/f[0];
space[1] = 1.0/f[1];
space[2] = 1.0/f[2];
typedef typename InputImageType::SizeType::SizeValueType SizeValueType;
typename InputImageType::SizeType size;
size[0] = static_cast<SizeValueType>(res.Dim(0));
size[1] = static_cast<SizeValueType>(res.Dim(1));
size[2] = static_cast<SizeValueType>(res.Dim(2));
typename itk::OrientedImage< T, 3 >::Pointer input = itk::OrientedImage< T, 3 >::New();
typename itk::OrientedImage< T, 3 >::Pointer output = itk::OrientedImage< T, 3 >::New();
typename itk::Image< T, 3 >::IndexType ipos;
ipos[0] = 0; ipos[1] = 0; ipos[2] = 0;
typename itk::Image< T, 3 >::IndexType opos;
opos[0] = 0; opos[1] = 0; opos[2] = 0;
typename itk::Image< T, 3 >::RegionType ireg;
ireg.SetSize(size);
ireg.SetIndex(ipos);
input->SetRegions(ireg);
input->Allocate();
typename itk::Image< T, 3 >::RegionType oreg;
oreg.SetSize(size);
ireg.SetIndex(opos);
output->SetRegions(oreg);
output->Allocate();
for (size_t z = 0; z < res.Dim(2); z++)
for (size_t y = 0; y < res.Dim(1); y++)
for (size_t x = 0; x < res.Dim(0); x++) {
ipos[0] = x; ipos[1] = y; ipos[2] = z;
input->SetPixel (ipos, res.At(x,y,z));
}
typename ResampleFilterType::Pointer rs = ResampleFilterType::New();
rs->SetInput( input );
rs->SetTransform( trafo );
rs->SetInterpolator( linterp );
rs->SetOutputOrigin ( input->GetOrigin());
rs->SetOutputSpacing ( space );
rs->SetOutputDirection ( input->GetDirection());
rs->SetSize ( size );
rs->Update ();
output = rs->GetOutput();
res = Matrix<T> (res.Dim(0)*f[0], res.Dim(1)*f[1], res.Dim(2)*f[2]);
res.Res(0) = res.Res(0)/f[0];
res.Res(1) = res.Dim(1)/f[1];
res.Res(2) = res.Dim(2)/f[2];
for (size_t z = 0; z < res.Dim(2); z++)
for (size_t y = 0; y < res.Dim(1); y++)
for (size_t x = 0; x < res.Dim(0); x++) {
opos[0] = x; opos[1] = y; opos[2] = z;
res.At(x,y,z) = output->GetPixel (opos);
}
#else
printf ("ITK ERROR - Resampling not performed without ITK!\n");
#endif
return res;
}
int main( int argc, char *argv[] )
{
string input_name;
string output_dir;
if (argc == 3) {
input_name = argv[1];
output_dir = argv[2];
}
const unsigned int Dimension = 3;
const unsigned int OutDimension = 2;
typedef short InputPixelType;
typedef int FilterPixelType;
typedef itk::Image< InputPixelType, Dimension > InputImageType;
typedef itk::Image< FilterPixelType, Dimension > FilterImageType;
typedef itk::Image< FilterPixelType, OutDimension > OutFilterImageType;
InputImageType::Pointer image;
itk::MetaDataDictionary dict;
if (input_name.size() && output_dir.size())
{
if (boost::filesystem::is_regular_file( input_name )) {
typedef itk::ImageFileReader< InputImageType > ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName( input_name );
try
{
reader->Update();
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ERROR: ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
image = reader->GetOutput();
dict = reader->GetMetaDataDictionary();
} else if (boost::filesystem::is_directory( input_name )) {
itkBasic::SeriesReader sreader( input_name );
sreader.readSeriesData( 2 );
try
{
itkBasic::ReaderType::Pointer imageReader = itkBasic::ReaderType::New();
itkBasic::FileNamesContainer fc;
sreader.getSeriesFileNames(0, fc);
image = itkBasic::getDicomSerie( fc, imageReader, 1 );
dict = *((*imageReader->GetMetaDataDictionaryArray())[0]);
}
catch( itk::ExceptionObject & err )
{
std::cerr << "ERROR: ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
}
}
if (!image) {
std::cerr << argv[0] << ": input output" << std::endl;
exit(1);
}
typedef itk::SigmoidImageFilter< InputImageType, FilterImageType > SigmoidCasterType;
SigmoidCasterType::Pointer sigmoidcaster = SigmoidCasterType::New();
sigmoidcaster->SetInput( image );
sigmoidcaster->SetOutputMaximum( 4000 );
sigmoidcaster->SetOutputMinimum( 1000 );
typedef itk::AccumulateImageFilter< FilterImageType, FilterImageType > AccumulateFilter;
AccumulateFilter::Pointer accumulator = AccumulateFilter::New();
accumulator->SetAccumulateDimension(1);
accumulator->SetInput( sigmoidcaster->GetOutput() );
typedef itk::ExtractImageFilter< FilterImageType, OutFilterImageType > ExtractFilter;
ExtractFilter::Pointer extractor = ExtractFilter::New();
extractor->SetInput( accumulator->GetOutput() );
FilterImageType::Pointer accuOut = accumulator->GetOutput();
accuOut->UpdateOutputInformation();
FilterImageType::RegionType extractRegion = accuOut->GetLargestPossibleRegion();
extractRegion.SetSize(1,0);
extractor->SetExtractionRegion( extractRegion );
typedef itk::ResampleImageFilter<OutFilterImageType, OutFilterImageType > ResampleFilter;
ResampleFilter::Pointer resampler = ResampleFilter::New();
resampler->SetInput( extractor->GetOutput() );
typedef itk::BSplineInterpolateImageFunction< OutFilterImageType > InterpolatorType;
InterpolatorType::Pointer interpolator = InterpolatorType::New();
interpolator->SetSplineOrder(3);
resampler->SetInterpolator( interpolator );
OutFilterImageType::Pointer exOut = extractor->GetOutput();
exOut->UpdateOutputInformation();
typedef itk::CenteredRigid2DTransform< double > TransformType;
TransformType::Pointer transform = TransformType::New();
transform->SetIdentity();
OutFilterImageType::PointType exOutCenter = exOut->GetOrigin();
exOutCenter[0] += (exOut->GetLargestPossibleRegion().GetSize()[0]-1) * exOut->GetSpacing()[0] *.5;
exOutCenter[1] += (exOut->GetLargestPossibleRegion().GetSize()[1]-1) * exOut->GetSpacing()[1] *.5;
transform->SetCenter( exOutCenter );
transform->SetAngleInDegrees( 180 );
resampler->SetTransform( transform );
resampler->SetOutputParametersFromImage( exOut );
OutFilterImageType::SpacingType resampleSpacing = exOut->GetSpacing();
resampleSpacing.Fill( std::min( resampleSpacing[0], resampleSpacing[1] ) );
OutFilterImageType::SizeType resampleSize;
resampleSize[0] = exOut->GetLargestPossibleRegion().GetSize()[0] * exOut->GetSpacing()[0] / resampleSpacing[0];
resampleSize[1] = exOut->GetLargestPossibleRegion().GetSize()[1] * exOut->GetSpacing()[1] / resampleSpacing[1];
resampler->SetSize( resampleSize );
resampler->SetOutputSpacing( resampleSpacing );
OutFilterImageType::Pointer result = resampler->GetOutput();
sigmoidcaster->SetBeta( -500 );
sigmoidcaster->SetAlpha( 5 );
result->Update();
int outDicomIndex = 0;
itk::EncapsulateMetaData( dict, "0008|0008", string("DERIVED\\SECONDARY\\AXIAL"));
boost::filesystem::path outpath = output_dir;
outpath = outpath / "IM%06d";
std::vector< itk::MetaDataDictionary* > dictArray;
dictArray.push_back(&dict);
itkBasic::writeDicomSeries( itkBasic::ImageRescale(itkBasic::ImageSharp(result, 0.5), -1000, 4000), outpath.string(), &dictArray, outDicomIndex);
// itkBasic::ImageSave( itkBasic::ImageSharp(result, 0.5), boost::str( boost::format("%s.%s.png") % output_name % "lung" ), 1, 0); // Auto Level
sigmoidcaster->SetBeta( 1000 );
sigmoidcaster->SetAlpha( 300 );
result->Update();
itkBasic::writeDicomSeries( itkBasic::ImageRescale(itkBasic::ImageSharp(result, 0.5), -1000, 4000), outpath.string(), &dictArray, outDicomIndex);
// itkBasic::ImageSave( itkBasic::ImageSharp(result, 0.5), boost::str( boost::format("%s.%s.png") % output_name % "bone" ), 1, 0); // Auto Level
sigmoidcaster->SetBeta( 0 );
sigmoidcaster->SetAlpha( 2000 );
result->Update();
itkBasic::writeDicomSeries( itkBasic::ImageRescale(itkBasic::ImageSharp(result, 0.5), -1000, 4000), outpath.string(), &dictArray, outDicomIndex);
// itkBasic::ImageSave( itkBasic::ImageSharp(result, 0.5), boost::str( boost::format("%s.%s.png") % output_name % "normal" ), 1, 0); // Auto Level
}
bool mitk::NavigationDataLandmarkTransformFilter::FindCorrespondentLandmarks(LandmarkPointContainer& sources, const LandmarkPointContainer& targets) const
{
if (sources.size() < 6 || targets.size() < 6)
return false;
//throw std::invalid_argument("ICP correspondence finding needs at least 6 landmarks");
/* lots of type definitions */
typedef itk::PointSet<mitk::ScalarType, 3> PointSetType;
//typedef itk::BoundingBox<PointSetType::PointIdentifier, PointSetType::PointDimension> BoundingBoxType;
typedef itk::EuclideanDistancePointMetric< PointSetType, PointSetType> MetricType;
//typedef MetricType::TransformType TransformBaseType;
//typedef MetricType::TransformType::ParametersType ParametersType;
//typedef TransformBaseType::JacobianType JacobianType;
//typedef itk::Euler3DTransform< double > TransformType;
typedef itk::VersorRigid3DTransform< double > TransformType;
typedef TransformType ParametersType;
typedef itk::PointSetToPointSetRegistrationMethod< PointSetType, PointSetType > RegistrationType;
/* copy landmarks to itk pointsets for registration */
PointSetType::Pointer sourcePointSet = PointSetType::New();
unsigned int i = 0;
for (LandmarkPointContainer::const_iterator it = sources.begin(); it != sources.end(); ++it)
{
PointSetType::PointType doublePoint;
mitk::itk2vtk(*it, doublePoint); // copy mitk::ScalarType point into double point as workaround to ITK 3.10 bug
sourcePointSet->SetPoint(i++, doublePoint /**it*/);
}
i = 0;
PointSetType::Pointer targetPointSet = PointSetType::New();
for (LandmarkPointContainer::const_iterator it = targets.begin(); it != targets.end(); ++it)
{
PointSetType::PointType doublePoint;
mitk::itk2vtk(*it, doublePoint); // copy mitk::ScalarType point into double point as workaround to ITK 3.10 bug
targetPointSet->SetPoint(i++, doublePoint /**it*/);
}
/* get centroid and extends of our pointsets */
//BoundingBoxType::Pointer sourceBoundingBox = BoundingBoxType::New();
//sourceBoundingBox->SetPoints(sourcePointSet->GetPoints());
//sourceBoundingBox->ComputeBoundingBox();
//BoundingBoxType::Pointer targetBoundingBox = BoundingBoxType::New();
//targetBoundingBox->SetPoints(targetPointSet->GetPoints());
//targetBoundingBox->ComputeBoundingBox();
TransformType::Pointer transform = TransformType::New();
transform->SetIdentity();
//transform->SetTranslation(targetBoundingBox->GetCenter() - sourceBoundingBox->GetCenter());
itk::LevenbergMarquardtOptimizer::Pointer optimizer = itk::LevenbergMarquardtOptimizer::New();
optimizer->SetUseCostFunctionGradient(false);
RegistrationType::Pointer registration = RegistrationType::New();
// Scale the translation components of the Transform in the Optimizer
itk::LevenbergMarquardtOptimizer::ScalesType scales(transform->GetNumberOfParameters());
const double translationScale = 5000; //sqrtf(targetBoundingBox->GetDiagonalLength2()) * 1000; // dynamic range of translations
const double rotationScale = 1.0; // dynamic range of rotations
scales[0] = 1.0 / rotationScale;
scales[1] = 1.0 / rotationScale;
scales[2] = 1.0 / rotationScale;
scales[3] = 1.0 / translationScale;
scales[4] = 1.0 / translationScale;
scales[5] = 1.0 / translationScale;
//scales.Fill(0.01);
unsigned long numberOfIterations = 80000;
double gradientTolerance = 1e-10; // convergence criterion
double valueTolerance = 1e-10; // convergence criterion
double epsilonFunction = 1e-10; // convergence criterion
optimizer->SetScales( scales );
optimizer->SetNumberOfIterations( numberOfIterations );
optimizer->SetValueTolerance( valueTolerance );
optimizer->SetGradientTolerance( gradientTolerance );
optimizer->SetEpsilonFunction( epsilonFunction );
registration->SetInitialTransformParameters( transform->GetParameters() );
//------------------------------------------------------
// Connect all the components required for Registration
//------------------------------------------------------
MetricType::Pointer metric = MetricType::New();
registration->SetMetric( metric );
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetFixedPointSet( targetPointSet );
registration->SetMovingPointSet( sourcePointSet );
try
{
//registration->StartRegistration();
registration->Update();
}
catch( itk::ExceptionObject & e )
{
MITK_INFO << "Exception caught during ICP optimization: " << e;
return false;
//throw e;
}
MITK_INFO << "ICP successful: Solution = " << transform->GetParameters() << std::endl;
MITK_INFO << "Metric value: " << metric->GetValue(transform->GetParameters());
/* find point correspondences */
//mitk::PointLocator::Pointer pointLocator = mitk::PointLocator::New(); // <<- use mitk::PointLocator instead of searching manually?
//pointLocator->SetPoints()
for (LandmarkPointContainer::const_iterator sourcesIt = sources.begin(); sourcesIt != sources.end(); ++sourcesIt)
{
}
//MetricType::MeasureType closestDistances = metric->GetValue(transform->GetParameters());
//unsigned int index = 0;
LandmarkPointContainer sortedSources;
for (LandmarkPointContainer::const_iterator targetsIt = targets.begin(); targetsIt != targets.end(); ++targetsIt)
{
double minDistance = itk::NumericTraits<double>::max();
LandmarkPointContainer::iterator minDistanceIterator = sources.end();
for (LandmarkPointContainer::iterator sourcesIt = sources.begin(); sourcesIt != sources.end(); ++sourcesIt)
{
TransformInitializerType::LandmarkPointType transformedSource = transform->TransformPoint(*sourcesIt);
double dist = targetsIt->EuclideanDistanceTo(transformedSource);
MITK_INFO << "target: " << *targetsIt << ", source: " << *sourcesIt << ", transformed source: " << transformedSource << ", dist: " << dist;
if (dist < minDistance )
{
minDistanceIterator = sourcesIt;
minDistance = dist;
}
}
if (minDistanceIterator == sources.end())
return false;
MITK_INFO << "minimum distance point is: " << *minDistanceIterator << " (dist: " << targetsIt->EuclideanDistanceTo(transform->TransformPoint(*minDistanceIterator)) << ", minDist: " << minDistance << ")";
sortedSources.push_back(*minDistanceIterator); // this point is assigned
sources.erase(minDistanceIterator); // erase it from sources to avoid duplicate assigns
}
//for (LandmarkPointContainer::const_iterator sortedSourcesIt = sortedSources.begin(); targetsIt != sortedSources.end(); ++targetsIt)
sources = sortedSources;
return true;
}
