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Examples/RegistrationITKv3/ImageRegistration18.cxx
/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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 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
:
typedef
CommandIterationUpdate
Self
;
typedef
itk::Command
Superclass
;
typedef
itk::SmartPointer<Self>
Pointer
;
itkNewMacro( Self );
protected
:
CommandIterationUpdate() {};
public
:
typedef
itk::RegularStepGradientDescentOptimizer
OptimizerType;
typedef
const
OptimizerType * OptimizerPointer;
void
Execute
(
itk::Object
*caller,
const
itk::EventObject
& event)
{
Execute
( (
const
itk::Object
*)caller, event);
}
void
Execute
(
const
itk::Object
*
object
,
const
itk::EventObject
& event)
{
OptimizerPointer 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;
}
const
unsigned
int
Dimension = 2;
typedef
unsigned
short
PixelType;
typedef
itk::Image< PixelType, Dimension >
FixedImageType;
typedef
itk::Image< PixelType, Dimension >
MovingImageType;
typedef
itk::TranslationTransform< double, Dimension >
TransformType;
typedef
itk::RegularStepGradientDescentOptimizer
OptimizerType;
typedef
itk::LinearInterpolateImageFunction
<
MovingImageType,
double
> InterpolatorType;
typedef
itk::ImageRegistrationMethod
<
FixedImageType,
MovingImageType > RegistrationType;
typedef
itk::GradientDifferenceImageToImageMetric
<
FixedImageType,
MovingImageType > MetricType;
TransformType::Pointer transform = TransformType::New();
OptimizerType::Pointer optimizer = OptimizerType::New();
InterpolatorType::Pointer interpolator = InterpolatorType::New();
RegistrationType::Pointer registration = RegistrationType::New();
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetInterpolator( interpolator );
MetricType::Pointer metric = MetricType::New();
metric->SetDerivativeDelta( 0.5 );
registration->SetMetric( metric );
typedef
itk::ImageFileReader< FixedImageType >
FixedImageReaderType;
typedef
itk::ImageFileReader< MovingImageType >
MovingImageReaderType;
FixedImageReaderType::Pointer fixedImageReader = FixedImageReaderType::New();
MovingImageReaderType::Pointer 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() );
typedef
RegistrationType::ParametersType 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] = atof( argv[4] );
}
if
( argc > 5 )
{
initialParameters[1] = atof( 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();
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
try
{
registration->Update();
std::cout <<
"Optimizer stop condition: "
<< registration->GetOptimizer()->GetStopConditionDescription()
<< std::endl;
}
catch
(
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.
//
typedef
itk::ResampleImageFilter
<
MovingImageType,
FixedImageType > ResampleFilterType;
TransformType::Pointer finalTransform = TransformType::New();
finalTransform->SetParameters( finalParameters );
finalTransform->SetFixedParameters( transform->GetFixedParameters() );
ResampleFilterType::Pointer resample = ResampleFilterType::New();
resample->SetTransform( finalTransform );
resample->SetInput( movingImageReader->GetOutput() );
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
//
typedef
unsigned
char
OutputPixelType;
typedef
itk::Image< OutputPixelType, Dimension >
OutputImageType;
typedef
itk::CastImageFilter
<
FixedImageType,
OutputImageType > CastFilterType;
typedef
itk::ImageFileWriter< OutputImageType >
WriterType;
WriterType::Pointer writer = WriterType::New();
CastFilterType::Pointer caster = CastFilterType::New();
writer->SetFileName( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->Update();
return
EXIT_SUCCESS;
}
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