BoundingBoxType::Pointer SBImageUtils::GetBoundingBox(ImageType::Pointer image)
{
ConstIteratorType constIterator(image, image->GetLargestPossibleRegion());
IteratorType iterator(image, image->GetLargestPossibleRegion());
PointSetType::Pointer pointSet = PointSetType::New();
PointsContainerPointer points = pointSet->GetPoints();
int pointCounter=0;
for (iterator.GoToBegin(), constIterator.GoToBegin(); !iterator.IsAtEnd(); ++iterator, ++constIterator) {
if(constIterator.Value() == 0)
{
ImageType::IndexType index = constIterator.GetIndex();
PointType point;
point[0] = index[0];
point[1] = index[1];
points->InsertElement(pointCounter, point);
pointCounter++;
}
}
BoundingBoxType::Pointer boundingBox = BoundingBoxType::New();
boundingBox->SetPoints(points);
boundingBox->ComputeBoundingBox();
return boundingBox;
}
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;
}
/*
* mexFunction(): entry point for the mex function
*/
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) {
// interface to deal with input arguments from Matlab
enum InputIndexType {IN_TRI, IN_X, IN_RES, IN_SIZE, IN_ORIGIN, InputIndexType_MAX};
MatlabImportFilter::Pointer matlabImport = MatlabImportFilter::New();
matlabImport->ConnectToMatlabFunctionInput(nrhs, prhs);
// check the number of input arguments
matlabImport->CheckNumberOfArguments(2, InputIndexType_MAX);
// register the inputs for this function at the import filter
typedef MatlabImportFilter::MatlabInputPointer MatlabInputPointer;
MatlabInputPointer inTRI = matlabImport->RegisterInput(IN_TRI, "TRI");
MatlabInputPointer inX = matlabImport->RegisterInput(IN_X, "X"); // (x, y, z)
MatlabInputPointer inRES = matlabImport->RegisterInput(IN_RES, "RES"); // (r, c, s)
MatlabInputPointer inSIZE = matlabImport->RegisterInput(IN_SIZE, "SIZE"); // (r, c, s)
MatlabInputPointer inORIGIN = matlabImport->RegisterInput(IN_ORIGIN, "ORIGIN"); // (x, y, z)
// interface to deal with outputs to Matlab
enum OutputIndexType {OUT_IM, OutputIndexType_MAX};
MatlabExportFilter::Pointer matlabExport = MatlabExportFilter::New();
matlabExport->ConnectToMatlabFunctionOutput(nlhs, plhs);
// check that the number of outputs the user is asking for is valid
matlabExport->CheckNumberOfArguments(0, OutputIndexType_MAX);
// register the outputs for this function at the export filter
typedef MatlabExportFilter::MatlabOutputPointer MatlabOutputPointer;
MatlabOutputPointer outIM = matlabExport->RegisterOutput(OUT_IM, "IM");
// if any input point set is empty, the outputs are empty too
if (mxIsEmpty(inTRI->pm) || mxIsEmpty(inX->pm)) {
matlabExport->CopyEmptyArrayToMatlab(outIM);
return;
}
// get number of rows in inputs X and TRI
mwSize nrowsX = mxGetM(inX->pm);
mwSize nrowsTRI = mxGetM(inTRI->pm);
// instantiate mesh
MeshType::Pointer mesh = MeshType::New();
// read vertices
PointSetType::Pointer xDef = PointSetType::New(); // default: empty point set
PointSetType::Pointer x = PointSetType::New();
x->GetPoints()->CastToSTLContainer()
= matlabImport->ReadVectorOfVectorsFromMatlab<PointType::CoordRepType, PointType>
(inX, xDef->GetPoints()->CastToSTLContainer());
#ifdef DEBUG
std::cout << "Number of X points read = " << x->GetNumberOfPoints() << std::endl;
#endif
// assertion check
if (nrowsX != x->GetNumberOfPoints()) {
mexErrMsgTxt(("Input " + inX->name
+ ": Number of points read different from number of points provided by user").c_str());
}
// swap XY coordinates to make them compliant with ITK convention
// (see important programming note at the help header above)
matlabImport->SwapXYInVectorOfVectors<PointType::CoordRepType, std::vector<PointType> >
(x->GetPoints()->CastToSTLContainer(), x->GetNumberOfPoints());
// populate mesh with vertices
mesh->SetPoints(x->GetPoints());
// read triangles
PointType triDef;
triDef.Fill(mxGetNaN());
for (mwIndex i = 0; i < nrowsTRI; ++i) {
PointType triangle = matlabImport->ReadRowVectorFromMatlab<CoordType, PointType>(inTRI, i, triDef);
// create a triangle cell to read the vertex indices of the current input triangle
CellAutoPointer cell;
cell.TakeOwnership(new TriangleType);
// assign to the 0, 1, 2 elements in the triangle cell the vertex
// indices that we have just read. Note that we have to substract
// 1 to convert Matlab's index convention 1, 2, 3, ... to C++
// convention 0, 1, 2, ...
cell->SetPointId(0, triangle[0] - 1);
cell->SetPointId(1, triangle[1] - 1);
cell->SetPointId(2, triangle[2] - 1);
// insert cell into the mesh
mesh->SetCell(i, cell);
}
#ifdef DEBUG
std::cout << "Number of triangles read = " << mesh->GetNumberOfCells() << std::endl;
#endif
// assertion check
if (nrowsTRI != mesh->GetNumberOfCells()) {
mexErrMsgTxt(("Input " + inTRI->name
+ ": Number of triangles read different from number of triangles provided by user").c_str());
}
// get user input parameters for the output rasterization
ImageType::SpacingType spacingDef;
spacingDef.Fill(1.0);
ImageType::SpacingType spacing = matlabImport->
ReadRowVectorFromMatlab<ImageType::SpacingValueType, ImageType::SpacingType>(inRES, spacingDef);
ImageType::SizeType sizeDef;
sizeDef.Fill(10);
ImageType::SizeType size = matlabImport->
ReadRowVectorFromMatlab<ImageType::SizeValueType, ImageType::SizeType>(inSIZE, sizeDef);
ImageType::PointType originDef;
originDef.Fill(0.0);
ImageType::PointType origin = matlabImport->
ReadRowVectorFromMatlab<ImageType::PointType::ValueType, ImageType::PointType>(inORIGIN, originDef);
// (see important programming note at the help header above)
matlabImport->SwapXYInVector<ImageType::PointType::ValueType, ImageType::PointType>(origin);
// instantiate rasterization filter
MeshFilterType::Pointer meshFilter = MeshFilterType::New();
// smallest voxel side length
ImageType::SpacingValueType minSpacing = spacing[0];
for (mwIndex i = 1; i < Dimension; ++i) {
minSpacing = std::min(minSpacing, spacing[i]);
}
// pass input parameters to the filter
meshFilter->SetInput(mesh);
meshFilter->SetSpacing(spacing);
meshFilter->SetSize(size);
meshFilter->SetOrigin(origin);
meshFilter->SetTolerance(minSpacing / 10.0);
meshFilter->SetInsideValue(1);
meshFilter->SetOutsideValue(0);
ImageType::IndexType start;
start.Fill(0);
meshFilter->SetIndex(start);
// convert image size from itk::Size format to std::vector<mwSize>
// so that we can use it in GraftItkImageOntoMatlab
std::vector<mwSize> sizeStdVector(Dimension);
for (unsigned int i = 0; i < Dimension; ++i) {
sizeStdVector[i] = size[i];
}
// graft ITK filter output onto Matlab output
matlabExport->GraftItkImageOntoMatlab<PixelType, Dimension>
(outIM, meshFilter->GetOutput(), sizeStdVector);
#ifdef DEBUG
std::cout << "Resolution (spacing) = " << meshFilter->GetSpacing() << std::endl;
std::cout << "Size = " << meshFilter->GetSize() << std::endl;
std::cout << "Origin = " << meshFilter->GetOrigin() << std::endl;
#endif
// run rasterization
meshFilter->Update();
}
