ITK  5.0.0
Insight Segmentation and Registration Toolkit
Examples/RegistrationITKv3/MultiResImageRegistration3.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.
*
*=========================================================================*/
//
// This example is the 3D version of the 2D example in MultiResImageRegistration1.cxx
//
#include "itkImage.h"
#include "itkCommand.h"
template <typename TRegistration>
class RegistrationInterfaceCommand : public itk::Command
{
public:
using Self = RegistrationInterfaceCommand;
using Superclass = itk::Command;
using Pointer = itk::SmartPointer<Self>;
itkNewMacro( Self );
protected:
RegistrationInterfaceCommand() {};
public:
using RegistrationType = TRegistration;
using RegistrationPointer = RegistrationType *;
using OptimizerPointer = OptimizerType *;
void Execute(itk::Object * object, const itk::EventObject & event) override
{
if( !(itk::IterationEvent().CheckEvent( &event )) )
{
return;
}
RegistrationPointer registration = static_cast<RegistrationPointer>( object );
OptimizerPointer optimizer = static_cast< OptimizerPointer >( registration->GetModifiableOptimizer() );
std::cout << "-------------------------------------" << std::endl;
std::cout << "MultiResolution Level : "
<< registration->GetCurrentLevel() << std::endl;
std::cout << std::endl;
if ( registration->GetCurrentLevel() == 0 )
{
optimizer->SetMaximumStepLength( 16.00 );
optimizer->SetMinimumStepLength( 0.01 );
}
else
{
optimizer->SetMaximumStepLength( optimizer->GetMaximumStepLength() / 4.0 );
optimizer->SetMinimumStepLength( optimizer->GetMinimumStepLength() / 10.0 );
}
}
void Execute(const itk::Object * , const itk::EventObject & ) override
{ return; }
};
// The following section of code implements an observer
// that will monitor the evolution of the registration process.
//
class CommandIterationUpdate : public itk::Command
{
public:
using Self = CommandIterationUpdate;
using Superclass = itk::Command;
using Pointer = itk::SmartPointer<Self>;
itkNewMacro( Self );
protected:
CommandIterationUpdate() {};
public:
using OptimizerPointer = const OptimizerType *;
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 < 4 )
{
std::cerr << "Missing Parameters " << std::endl;
std::cerr << "Usage: " << argv[0];
std::cerr << " fixedImageFile movingImageFile ";
std::cerr << " outputImagefile [backgroundGrayLevel]";
std::cerr << " [checkerBoardBefore] [checkerBoardAfter]";
std::cerr << " [useExplicitPDFderivatives ] " << std::endl;
std::cerr << " [numberOfBins] [numberOfSamples ] " << std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int Dimension = 3;
using PixelType = unsigned short;
using FixedImageType = itk::Image< PixelType, Dimension >;
using MovingImageType = itk::Image< PixelType, Dimension >;
using InternalPixelType = float;
using InternalImageType = itk::Image< InternalPixelType, Dimension >;
using InterpolatorType = itk::LinearInterpolateImageFunction<
InternalImageType,
double >;
InternalImageType,
InternalImageType >;
InternalImageType,
InternalImageType >;
using FixedImagePyramidType = itk::MultiResolutionPyramidImageFilter<
InternalImageType,
InternalImageType >;
using MovingImagePyramidType = itk::MultiResolutionPyramidImageFilter<
InternalImageType,
InternalImageType >;
// All the components are instantiated using their \code{New()} method
// and connected to the registration object as in previous example.
//
TransformType::Pointer transform = TransformType::New();
OptimizerType::Pointer optimizer = OptimizerType::New();
InterpolatorType::Pointer interpolator = InterpolatorType::New();
RegistrationType::Pointer registration = RegistrationType::New();
MetricType::Pointer metric = MetricType::New();
FixedImagePyramidType::Pointer fixedImagePyramid =
FixedImagePyramidType::New();
MovingImagePyramidType::Pointer movingImagePyramid =
MovingImagePyramidType::New();
registration->SetOptimizer( optimizer );
registration->SetTransform( transform );
registration->SetInterpolator( interpolator );
registration->SetMetric( metric );
registration->SetFixedImagePyramid( fixedImagePyramid );
registration->SetMovingImagePyramid( movingImagePyramid );
using FixedImageReaderType = itk::ImageFileReader< FixedImageType >;
using MovingImageReaderType = itk::ImageFileReader< MovingImageType >;
FixedImageReaderType::Pointer fixedImageReader = FixedImageReaderType::New();
MovingImageReaderType::Pointer movingImageReader = MovingImageReaderType::New();
fixedImageReader->SetFileName( argv[1] );
movingImageReader->SetFileName( argv[2] );
using FixedCastFilterType = itk::CastImageFilter<
FixedImageType, InternalImageType >;
using MovingCastFilterType = itk::CastImageFilter<
MovingImageType, InternalImageType >;
FixedCastFilterType::Pointer fixedCaster = FixedCastFilterType::New();
MovingCastFilterType::Pointer movingCaster = MovingCastFilterType::New();
fixedCaster->SetInput( fixedImageReader->GetOutput() );
movingCaster->SetInput( movingImageReader->GetOutput() );
registration->SetFixedImage( fixedCaster->GetOutput() );
registration->SetMovingImage( movingCaster->GetOutput() );
fixedCaster->Update();
registration->SetFixedImageRegion(
fixedCaster->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
initialParameters[2] = 0.0; // Initial offset in mm along Z
registration->SetInitialTransformParameters( initialParameters );
metric->SetNumberOfHistogramBins( 128 );
metric->SetNumberOfSpatialSamples( 50000 );
if( argc > 8 )
{
// optionally, override the values with numbers taken from the command line arguments.
metric->SetNumberOfHistogramBins( std::stoi( argv[8] ) );
}
if( argc > 9 )
{
// optionally, override the values with numbers taken from the command line arguments.
metric->SetNumberOfSpatialSamples( std::stoi( argv[9] ) );
}
metric->ReinitializeSeed( 76926294 );
if( argc > 7 )
{
// Define whether to calculate the metric derivative by explicitly
// computing the derivatives of the joint PDF with respect to the Transform
// parameters, or doing it by progressively accumulating contributions from
// each bin in the joint PDF.
metric->SetUseExplicitPDFDerivatives( std::stoi( argv[7] ) );
}
optimizer->SetNumberOfIterations( 200 );
optimizer->SetRelaxationFactor( 0.9 );
// Create the Command observer and register it with the optimizer.
//
CommandIterationUpdate::Pointer observer = CommandIterationUpdate::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
using CommandType = RegistrationInterfaceCommand<RegistrationType>;
CommandType::Pointer command = CommandType::New();
registration->AddObserver( itk::IterationEvent(), command );
registration->SetNumberOfLevels( 3 );
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();
double TranslationAlongX = finalParameters[0];
double TranslationAlongY = finalParameters[1];
double TranslationAlongZ = finalParameters[2];
unsigned int numberOfIterations = optimizer->GetCurrentIteration();
double bestValue = optimizer->GetValue();
// Print out results
//
std::cout << "Result = " << std::endl;
std::cout << " Translation X = " << TranslationAlongX << std::endl;
std::cout << " Translation Y = " << TranslationAlongY << std::endl;
std::cout << " Translation Z = " << TranslationAlongZ << std::endl;
std::cout << " Iterations = " << numberOfIterations << std::endl;
std::cout << " Metric value = " << bestValue << std::endl;
using ResampleFilterType = itk::ResampleImageFilter<
MovingImageType,
FixedImageType >;
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();
PixelType backgroundGrayLevel = 100;
if( argc > 4 )
{
backgroundGrayLevel = std::stoi( argv[4] );
}
resample->SetSize( fixedImage->GetLargestPossibleRegion().GetSize() );
resample->SetOutputOrigin( fixedImage->GetOrigin() );
resample->SetOutputSpacing( fixedImage->GetSpacing() );
resample->SetOutputDirection( fixedImage->GetDirection() );
resample->SetDefaultPixelValue( backgroundGrayLevel );
using OutputPixelType = unsigned char;
using CastFilterType = itk::CastImageFilter<
FixedImageType,
OutputImageType >;
WriterType::Pointer writer = WriterType::New();
CastFilterType::Pointer caster = CastFilterType::New();
writer->SetFileName( argv[3] );
caster->SetInput( resample->GetOutput() );
writer->SetInput( caster->GetOutput() );
writer->Update();
//
// Generate checkerboards before and after registration
//
using CheckerBoardFilterType = itk::CheckerBoardImageFilter< FixedImageType >;
CheckerBoardFilterType::Pointer checker = CheckerBoardFilterType::New();
checker->SetInput1( fixedImage );
checker->SetInput2( resample->GetOutput() );
caster->SetInput( checker->GetOutput() );
writer->SetInput( caster->GetOutput() );
resample->SetDefaultPixelValue( 0 );
// Before registration
TransformType::Pointer identityTransform = TransformType::New();
identityTransform->SetIdentity();
resample->SetTransform( identityTransform );
if( argc > 5 )
{
writer->SetFileName( argv[5] );
writer->Update();
}
// After registration
resample->SetTransform( finalTransform );
if( argc > 6 )
{
writer->SetFileName( argv[6] );
writer->Update();
}
return EXIT_SUCCESS;
}