ITK  5.4.0
Insight Toolkit
Examples/RegistrationITKv4/ModelToImageRegistration2.cxx
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* Copyright NumFOCUS
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* Licensed under the Apache License, Version 2.0 (the "License");
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// Software Guide : BeginLatex
//
// This example illustrates the use of the \doxygen{SpatialObject} as a
// component of the registration framework in order to perform model based
// registration. In this case, a SpatialObject is used for generating a
// \doxygen{PointSet} whose points are located in a narrow band around the
// edges of the SpatialObject. This PointSet is then used in order to perform
// PointSet to Image registration.
//
// Software Guide : EndLatex
// Software Guide : BeginLatex
//
// In this example we use the \doxygen{BoxSpatialObject}, that is one of the
// simplest SpatialObjects in ITK.
//
// \index{itk::BoxSpatialObject!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The generation of the PointSet is done in two stages. First the
// SpatialObject is rasterized in order to generate an image containing a
// binary mask that represents the inside and outside of the SpatialObject.
// Second, this mask is used for computing a distance map, and the points
// close to the boundary of the mask are taken as elements of the final
// PointSet. The pixel values associated to the point in the PointSet are the
// values of distance from each point to the binary mask. The first stage is
// performed by the \doxygen{SpatialObjectToImageFilter}, while the second
// stage is performed with the \doxygen{BinaryMaskToNarrowBandPointSetFilter}
//
// \index{itk::Spatial\-Object\-To\-Image\-Filter!header}
// \index{itk::Binary\-Mask\-To\-Narrow\-Band\-Point\-Set\-Filter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
#include "itkPointSet.h"
//
// Observer to the optimizer
//
class CommandIterationUpdate : public itk::Command
{
public:
using Self = CommandIterationUpdate;
itkNewMacro(Self);
protected:
CommandIterationUpdate() = default;
public:
using OptimizerPointer = const OptimizerType *;
void
Execute(itk::Object * caller, const itk::EventObject & event) override
{
Execute((const itk::Object *)caller, event);
}
void
Execute(const itk::Object * object, const itk::EventObject & event) override
{
auto optimizer = static_cast<OptimizerPointer>(object);
if (typeid(event) != typeid(itk::IterationEvent))
{
return;
}
OptimizerType::DerivativeType gradient = optimizer->GetGradient();
OptimizerType::ScalesType scales = optimizer->GetScales();
double magnitude2 = 0.0;
for (unsigned int i = 0; i < gradient.size(); ++i)
{
const double fc = gradient[i] / scales[i];
magnitude2 += fc * fc;
}
const double gradientMagnitude = std::sqrt(magnitude2);
std::cout << optimizer->GetCurrentIteration() << " ";
std::cout << optimizer->GetValue() << " ";
std::cout << gradientMagnitude << " ";
std::cout << optimizer->GetCurrentPosition() << std::endl;
}
};
int
main(int argc, char * argv[])
{
if (argc < 2)
{
std::cerr << "Missing argument" << std::endl;
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " movingImageFileName [initialX initialY] "
<< std::endl;
std::cerr << "[rasterizedObjectFileName] [BoxSizeX BoxSizeY]"
<< std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int Dimension = 2;
using MaskPixelType = unsigned char;
using MaskImageType = itk::Image<MaskPixelType, Dimension>;
using SpatialObjectType = itk::BoxSpatialObject<Dimension>;
using SpatialObjectToImageFilterType =
using FixedPointSetType = itk::PointSet<float, Dimension>;
using NarrowBandFilterType =
FixedPointSetType>;
using PixelType = short;
using MaskPixelType = unsigned char;
using MaskImageType = itk::Image<MaskPixelType, Dimension>;
using TransformType = itk::Rigid2DTransform<double>;
using ParametersType = TransformType::ParametersType;
using LinearInterpolatorType =
using MetricType =
ImageType>;
using OptimizerScalesType = OptimizerType::ScalesType;
using RegistrationType =
using IterationObserverType = CommandIterationUpdate;
using ImageReaderType = itk::ImageFileReader<ImageType>;
IterationObserverType::Pointer iterationObserver;
LinearInterpolatorType::Pointer linearInterpolator;
RegistrationType::Pointer registrationMethod;
ImageReaderType::Pointer movingImageReader;
NarrowBandFilterType::Pointer narrowBandPointSetFilter;
metric = MetricType::New();
transform = TransformType::New();
optimizer = OptimizerType::New();
linearInterpolator = LinearInterpolatorType::New();
registrationMethod = RegistrationType::New();
iterationObserver = IterationObserverType::New();
spatialObject = SpatialObjectType::New();
rasterizationFilter = SpatialObjectToImageFilterType::New();
narrowBandPointSetFilter = NarrowBandFilterType::New();
movingImageReader = ImageReaderType::New();
movingImageReader->SetFileName(argv[1]);
try
{
movingImageReader->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Problem reading Moving image from = " << std::endl;
std::cerr << argv[1] << std::endl;
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
movingImage = movingImageReader->GetOutput();
boxSize[0] = 60.0; // mm
boxSize[1] = 60.0; // mm
if (argc > 6)
{
boxSize[0] = std::stod(argv[5]);
boxSize[1] = std::stod(argv[6]);
}
//
// The geometry of the BoxSpatialObject is such that one of
// its corners is located at the origin of coordinates.
//
spatialObject->SetSizeInObjectSpace(boxSize);
ImageType::RegionType region = movingImage->GetLargestPossibleRegion();
ImageType::SizeType imageSize = region.GetSize();
ImageType::SpacingType spacing = movingImage->GetSpacing();
origin[0] = (boxSize[0] - imageSize[0] * spacing[0]) / 2.0;
origin[1] = (boxSize[1] - imageSize[1] * spacing[1]) / 2.0;
rasterizationFilter->SetInput(spatialObject);
rasterizationFilter->SetSize(imageSize);
rasterizationFilter->SetSpacing(spacing);
rasterizationFilter->SetOrigin(origin);
narrowBandPointSetFilter->SetBandWidth(5.0);
narrowBandPointSetFilter->SetInput(rasterizationFilter->GetOutput());
narrowBandPointSetFilter->Update();
if (argc > 4)
{
using MaskWriterType = itk::ImageFileWriter<MaskImageType>;
auto maskWriter = MaskWriterType::New();
maskWriter->SetInput(rasterizationFilter->GetOutput());
maskWriter->SetFileName(argv[4]);
maskWriter->Update();
}
fixedPointSet = narrowBandPointSetFilter->GetOutput();
fixedPointSet->Print(std::cout);
registrationMethod->SetOptimizer(optimizer);
registrationMethod->SetInterpolator(linearInterpolator);
registrationMethod->SetMetric(metric);
registrationMethod->SetTransform(transform);
registrationMethod->SetMovingImage(movingImage);
registrationMethod->SetFixedPointSet(fixedPointSet);
optimizer->SetMaximumStepLength(1.00);
optimizer->SetMinimumStepLength(0.001);
optimizer->SetNumberOfIterations(300);
optimizer->SetRelaxationFactor(0.90);
optimizer->SetGradientMagnitudeTolerance(0.05);
optimizer->MinimizeOn();
optimizer->AddObserver(itk::IterationEvent(), iterationObserver);
TransformType::TranslationType initialTranslation;
initialTranslation[0] = 0.0;
initialTranslation[1] = 0.0;
if (argc >= 4)
{
initialTranslation[0] = std::stod(argv[2]);
initialTranslation[1] = std::stod(argv[3]);
}
TransformType::OutputPointType rotationCenter;
rotationCenter[0] = boxSize[0] / 2.0;
rotationCenter[1] = boxSize[1] / 2.0;
transform->SetIdentity();
transform->SetCenter(rotationCenter);
transform->SetTranslation(initialTranslation);
registrationMethod->SetInitialTransformParameters(
transform->GetParameters());
OptimizerScalesType optimizerScales(transform->GetNumberOfParameters());
const double translationScale = 1.0 / 1000.0;
optimizerScales[0] = 1.0;
optimizerScales[1] = translationScale;
optimizerScales[2] = translationScale;
optimizer->SetScales(optimizerScales);
try
{
registrationMethod->Update();
std::cout
<< "Optimizer stop condition: "
<< registrationMethod->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Problem found during the registration" << std::endl;
std::cerr << argv[1] << std::endl;
std::cerr << excp << std::endl;
return EXIT_FAILURE;
}
ParametersType transformParameters =
registrationMethod->GetLastTransformParameters();
TransformType::OutputPointType center = transform->GetCenter();
std::cout << "Registration parameter = " << std::endl;
std::cout << "Rotation center = " << center << std::endl;
std::cout << "Parameters = " << transformParameters << std::endl;
return EXIT_SUCCESS;
}
Pointer
SmartPointer< Self > Pointer
Definition: itkAddImageFilter.h:93
ConstPointer
SmartPointer< const Self > ConstPointer
Definition: itkAddImageFilter.h:94
itk::PointSet
A superclass of the N-dimensional mesh structure; supports point (geometric coordinate and attribute)...
Definition: itkPointSet.h:82
itkRigid2DTransform.h
itkNormalizedCorrelationPointSetToImageMetric.h
itkRegularStepGradientDescentOptimizer.h
itk::GTest::TypedefsAndConstructors::Dimension2::PointType
ImageBaseType::PointType PointType
Definition: itkGTestTypedefsAndConstructors.h:51
itk::BinaryMaskToNarrowBandPointSetFilter
Generate a PointSet containing the narrow band around the edges of a input binary image.
Definition: itkBinaryMaskToNarrowBandPointSetFilter.h:54
itkImageFileReader.h
itk::GTest::TypedefsAndConstructors::Dimension2::SizeType
ImageBaseType::SizeType SizeType
Definition: itkGTestTypedefsAndConstructors.h:49
itk::SpatialObjectToImageFilter
Base class for filters that take a SpatialObject as input and produce an image as output....
Definition: itkSpatialObjectToImageFilter.h:41
itk::SmartPointer< Self >
itk::RegularStepGradientDescentOptimizer
Implement a gradient descent optimizer.
Definition: itkRegularStepGradientDescentOptimizer.h:33
itk::NormalizedCorrelationPointSetToImageMetric
Computes similarity between pixel values of a point set and intensity values of an image.
Definition: itkNormalizedCorrelationPointSetToImageMetric.h:44
itk::ImageFileReader
Data source that reads image data from a single file.
Definition: itkImageFileReader.h:75
itk::LinearInterpolateImageFunction
Linearly interpolate an image at specified positions.
Definition: itkLinearInterpolateImageFunction.h:51
itk::Command
Superclass for callback/observer methods.
Definition: itkCommand.h:45
itk::Rigid2DTransform
Rigid2DTransform of a vector space (e.g. space coordinates)
Definition: itkRigid2DTransform.h:56
itk::ImageFileWriter
Writes image data to a single file.
Definition: itkImageFileWriter.h:88
itkSpatialObjectToImageFilter.h
itk::Command
class ITK_FORWARD_EXPORT Command
Definition: itkObject.h:42
itk::GTest::TypedefsAndConstructors::Dimension2::RegionType
ImageBaseType::RegionType RegionType
Definition: itkGTestTypedefsAndConstructors.h:54
itk::Command::Execute
virtual void Execute(Object *caller, const EventObject &event)=0
itk::BoxSpatialObject
The class may be used to represent N-dimensional boxes. In two dimensions it is a rectangle,...
Definition: itkBoxSpatialObject.h:37
itk::PointSetToImageRegistrationMethod
Base class for PointSet to Image Registration Methods.
Definition: itkPointSetToImageRegistrationMethod.h:67
itkNearestNeighborInterpolateImageFunction.h
itkImageFileWriter.h
itkBoxSpatialObject.h
itk::Object
Base class for most ITK classes.
Definition: itkObject.h:61
itk::Image
Templated n-dimensional image class.
Definition: itkImage.h:88
itk::EventObject
Abstraction of the Events used to communicating among filters and with GUIs.
Definition: itkEventObject.h:57
itkBinaryMaskToNarrowBandPointSetFilter.h
itkPointSet.h
New
static Pointer New()
AddImageFilter
Definition: itkAddImageFilter.h:81
itkResampleImageFilter.h
itk::GTest::TypedefsAndConstructors::Dimension2::Dimension
constexpr unsigned int Dimension
Definition: itkGTestTypedefsAndConstructors.h:44
Superclass
BinaryGeneratorImageFilter< TInputImage1, TInputImage2, TOutputImage > Superclass
Definition: itkAddImageFilter.h:90
itkPointSetToImageRegistrationMethod.h
itk::Size::GetSize
const SizeValueType * GetSize() const
Definition: itkSize.h:171