ITK
5.2.0
Insight Toolkit
Examples/RegistrationITKv4/ModelToImageRegistration2.cxx
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
// 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
#include "
itkBoxSpatialObject.h
"
// 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 witht eh \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
#include "
itkSpatialObjectToImageFilter.h
"
#include "
itkBinaryMaskToNarrowBandPointSetFilter.h
"
// Software Guide : EndCodeSnippet
#include "
itkBinaryMaskToNarrowBandPointSetFilter.h
"
#include "
itkPointSet.h
"
#include "
itkPointSetToImageRegistrationMethod.h
"
#include "
itkNormalizedCorrelationPointSetToImageMetric.h
"
#include "
itkNearestNeighborInterpolateImageFunction.h
"
#include "
itkRigid2DTransform.h
"
#include "
itkRegularStepGradientDescentOptimizer.h
"
#include "
itkResampleImageFilter.h
"
#include "
itkImageFileReader.h
"
#include "
itkImageFileWriter.h
"
//
// Observer to the optimizer
//
class
CommandIterationUpdate :
public
itk::Command
{
public
:
using
Self = CommandIterationUpdate;
using
Superclass =
itk::Command
;
using
Pointer =
itk::SmartPointer<Self>
;
itkNewMacro(Self);
protected
:
CommandIterationUpdate() =
default
;
public
:
using
OptimizerType =
itk::RegularStepGradientDescentOptimizer
;
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 =
itk::SpatialObjectToImageFilter<SpatialObjectType, MaskImageType>
;
using
FixedPointSetType =
itk::PointSet<float, Dimension>
;
using
NarrowBandFilterType =
itk::BinaryMaskToNarrowBandPointSetFilter
<MaskImageType,
FixedPointSetType>;
using
PixelType =
signed
short;
using
ImageType =
itk::Image<PixelType, Dimension>
;
using
MaskPixelType =
unsigned
char;
using
MaskImageType =
itk::Image<MaskPixelType, Dimension>
;
using
TransformType =
itk::Rigid2DTransform<double>
;
using
ParametersType = TransformType::ParametersType;
using
OptimizerType =
itk::RegularStepGradientDescentOptimizer
;
using
LinearInterpolatorType =
itk::LinearInterpolateImageFunction<ImageType, double>
;
using
MetricType =
itk::NormalizedCorrelationPointSetToImageMetric
<FixedPointSetType,
ImageType>;
using
OptimizerScalesType = OptimizerType::ScalesType;
using
RegistrationType =
itk::PointSetToImageRegistrationMethod<FixedPointSetType, ImageType>
;
using
IterationObserverType = CommandIterationUpdate;
using
ImageReaderType =
itk::ImageFileReader<ImageType>
;
SpatialObjectType::Pointer spatialObject;
TransformType::Pointer transform;
OptimizerType::Pointer optimizer;
IterationObserverType::Pointer iterationObserver;
LinearInterpolatorType::Pointer linearInterpolator;
MetricType::Pointer metric;
RegistrationType::Pointer registrationMethod;
ImageReaderType::Pointer movingImageReader;
FixedPointSetType::Pointer fixedPointSet;
ImageType::ConstPointer movingImage;
SpatialObjectToImageFilterType::Pointer rasterizationFilter;
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();
SpatialObjectType::SizeType
boxSize;
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();
ImageType::PointType
origin;
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>
;
MaskWriterType::Pointer 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;
}
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:50
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:43
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:62
itk::Image
Templated n-dimensional image class.
Definition:
itkImage.h:86
itk::EventObject
Abstraction of the Events used to communicating among filters and with GUIs.
Definition:
itkEventObject.h:57
itkBinaryMaskToNarrowBandPointSetFilter.h
itkPointSet.h
itkResampleImageFilter.h
itk::GTest::TypedefsAndConstructors::Dimension2::Dimension
constexpr unsigned int Dimension
Definition:
itkGTestTypedefsAndConstructors.h:44
itkPointSetToImageRegistrationMethod.h
itk::Size::GetSize
const SizeValueType * GetSize() const
Definition:
itkSize.h:169
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