ITK
6.0.0
Insight Toolkit
Examples/RegistrationITKv4/ImageRegistration18.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
*
* https://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 how to use the
// \doxygen{GradientDifferenceImageToImageMetric}.
//
// This metric is particularly useful for registration scenarios where fitting
// the edges of both images is the most relevant criteria for registration
// success.
//
// \index{itk::ImageRegistrationMethod!Monitoring}
//
//
// Software Guide : EndLatex
#include "
itkImageRegistrationMethod.h
"
#include "
itkTranslationTransform.h
"
#include "
itkGradientDifferenceImageToImageMetric.h
"
#include "
itkRegularStepGradientDescentOptimizer.h
"
#include "
itkImageFileReader.h
"
#include "
itkImageFileWriter.h
"
#include "
itkCommand.h
"
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
(!itk::IterationEvent().CheckEvent(&event))
{
return
;
}
std::cout << optimizer->GetCurrentIteration() <<
" = "
;
std::cout << optimizer->GetValue() <<
" : "
;
std::cout << optimizer->GetCurrentPosition() << std::endl;
}
};
int
main(
int
argc,
char
* argv[])
{
if
(argc < 3)
{
std::cerr <<
"Missing Parameters "
<< std::endl;
std::cerr <<
"Usage: "
<< argv[0];
std::cerr <<
" fixedImageFile movingImageFile "
;
std::cerr <<
"outputImagefile"
<< std::endl;
std::cerr <<
"[initialTx] [initialTy]"
<< std::endl;
return
EXIT_FAILURE;
}
constexpr
unsigned
int
Dimension
= 2;
using
PixelType =
unsigned
short;
using
FixedImageType =
itk::Image<PixelType, Dimension>
;
using
MovingImageType =
itk::Image<PixelType, Dimension>
;
using
TransformType =
itk::TranslationTransform<double, Dimension>
;
using
OptimizerType =
itk::RegularStepGradientDescentOptimizer
;
using
InterpolatorType =
itk::LinearInterpolateImageFunction<MovingImageType, double>
;
using
RegistrationType =
itk::ImageRegistrationMethod<FixedImageType, MovingImageType>
;
using
MetricType =
itk::GradientDifferenceImageToImageMetric
<FixedImageType,
MovingImageType>;
auto
transform =
TransformType::New
();
auto
optimizer =
OptimizerType::New
();
auto
interpolator =
InterpolatorType::New
();
auto
registration =
RegistrationType::New
();
registration->SetOptimizer(optimizer);
registration->SetTransform(transform);
registration->SetInterpolator(interpolator);
auto
metric =
MetricType::New
();
metric->SetDerivativeDelta(0.5);
registration->SetMetric(metric);
using
FixedImageReaderType =
itk::ImageFileReader<FixedImageType>
;
using
MovingImageReaderType =
itk::ImageFileReader<MovingImageType>
;
auto
fixedImageReader =
FixedImageReaderType::New
();
auto
movingImageReader =
MovingImageReaderType::New
();
fixedImageReader->SetFileName(argv[1]);
movingImageReader->SetFileName(argv[2]);
registration->SetFixedImage(fixedImageReader->GetOutput());
registration->SetMovingImage(movingImageReader->GetOutput());
fixedImageReader
->Update();
// This is needed to make the BufferedRegion below valid.
registration->SetFixedImageRegion(
fixedImageReader->GetOutput()->GetBufferedRegion());
using
ParametersType = RegistrationType::ParametersType;
ParametersType initialParameters(transform->GetNumberOfParameters());
initialParameters[0] = 0.0;
// Initial offset in mm along X
initialParameters[1] = 0.0;
// Initial offset in mm along Y
if
(argc > 4)
{
initialParameters[0] = std::stod(argv[4]);
}
if
(argc > 5)
{
initialParameters[1] = std::stod(argv[5]);
}
std::cout <<
"Initial parameters = "
<< initialParameters << std::endl;
registration->SetInitialTransformParameters(initialParameters);
optimizer->SetMaximumStepLength(4.00);
optimizer->SetMinimumStepLength(0.01);
optimizer->SetNumberOfIterations(200);
optimizer->SetGradientMagnitudeTolerance(1
e
-40);
optimizer->MaximizeOn();
auto
observer =
CommandIterationUpdate::New
();
optimizer->AddObserver(itk::IterationEvent(), observer);
try
{
registration->Update();
std::cout <<
"Optimizer stop condition: "
<< registration->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
}
catch
(
const
itk::ExceptionObject
& err)
{
std::cout <<
"ExceptionObject caught !"
<< std::endl;
std::cout << err << std::endl;
return
EXIT_FAILURE;
}
ParametersType finalParameters = registration->GetLastTransformParameters();
const
double
TranslationAlongX = finalParameters[0];
const
double
TranslationAlongY = finalParameters[1];
const
unsigned
int
numberOfIterations = optimizer->GetCurrentIteration();
const
double
bestValue = optimizer->GetValue();
std::cout <<
"Registration done !"
<< std::endl;
std::cout <<
"Optimizer stop condition = "
<< registration->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
std::cout <<
"Number of iterations = "
<< numberOfIterations << std::endl;
std::cout <<
"Translation along X = "
<< TranslationAlongX << std::endl;
std::cout <<
"Translation along Y = "
<< TranslationAlongY << std::endl;
std::cout <<
"Optimal metric value = "
<< bestValue << std::endl;
// Prepare the resampling filter in order to map the moving image.
//
using
ResampleFilterType =
itk::ResampleImageFilter<MovingImageType, FixedImageType>
;
auto
finalTransform =
TransformType::New
();
finalTransform->SetParameters(finalParameters);
finalTransform->SetFixedParameters(transform->GetFixedParameters());
auto
resample =
ResampleFilterType::New
();
resample->SetTransform(finalTransform);
resample->SetInput(movingImageReader->GetOutput());
const
FixedImageType::Pointer
fixedImage = fixedImageReader->GetOutput();
resample->SetSize(fixedImage->GetLargestPossibleRegion().GetSize());
resample->SetOutputOrigin(fixedImage->GetOrigin());
resample->SetOutputSpacing(fixedImage->GetSpacing());
resample->SetOutputDirection(fixedImage->GetDirection());
resample->SetDefaultPixelValue(100);
// Prepare a writer and caster filters to send the resampled moving image to
// a file
//
using
OutputPixelType =
unsigned
char;
using
OutputImageType =
itk::Image<OutputPixelType, Dimension>
;
using
CastFilterType =
itk::CastImageFilter<FixedImageType, OutputImageType>
;
using
WriterType =
itk::ImageFileWriter<OutputImageType>
;
auto
writer =
WriterType::New
();
auto
caster =
CastFilterType::New
();
writer->SetFileName(argv[3]);
caster->SetInput(resample->GetOutput());
writer->SetInput(caster->GetOutput());
writer->Update();
return
EXIT_SUCCESS;
}
Pointer
SmartPointer< Self > Pointer
Definition:
itkAddImageFilter.h:93
itk::CastImageFilter
Casts input pixels to output pixel type.
Definition:
itkCastImageFilter.h:100
itkRegularStepGradientDescentOptimizer.h
itkImageFileReader.h
itk::GradientDifferenceImageToImageMetric
Computes similarity between two objects to be registered.
Definition:
itkGradientDifferenceImageToImageMetric.h:58
itk::ImageRegistrationMethod
Base class for Image Registration Methods.
Definition:
itkImageRegistrationMethod.h:70
itk::SmartPointer< Self >
itk::RegularStepGradientDescentOptimizer
Implement a gradient descent optimizer.
Definition:
itkRegularStepGradientDescentOptimizer.h:33
itkTranslationTransform.h
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::ImageFileWriter
Writes image data to a single file.
Definition:
itkImageFileWriter.h:90
itk::Command
class ITK_FORWARD_EXPORT Command
Definition:
itkObject.h:42
itk::TranslationTransform
Translation transformation of a vector space (e.g. space coordinates)
Definition:
itkTranslationTransform.h:43
itkImageRegistrationMethod.h
itk::Command::Execute
virtual void Execute(Object *caller, const EventObject &event)=0
itkImageFileWriter.h
itk::ExceptionObject
Standard exception handling object.
Definition:
itkExceptionObject.h:50
itk::ResampleImageFilter
Resample an image via a coordinate transform.
Definition:
itkResampleImageFilter.h:90
itk::Object
Base class for most ITK classes.
Definition:
itkObject.h:61
itk::Math::e
static constexpr double e
Definition:
itkMath.h:56
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:58
New
static Pointer New()
AddImageFilter
Definition:
itkAddImageFilter.h:81
itkGradientDifferenceImageToImageMetric.h
itk::GTest::TypedefsAndConstructors::Dimension2::Dimension
constexpr unsigned int Dimension
Definition:
itkGTestTypedefsAndConstructors.h:44
itkCommand.h
Superclass
BinaryGeneratorImageFilter< TInputImage1, TInputImage2, TOutputImage > Superclass
Definition:
itkAddImageFilter.h:90
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for ITK by
1.8.16