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/*=========================================================================
*
* 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.
*
*=========================================================================*/
#include "itkJensenHavrdaCharvatTsallisPointSetToPointSetMetricv4.h"
#include "itkGradientDescentOptimizerv4.h"
#include "itkTransform.h"
#include "itkAffineTransform.h"
#include "itkRegistrationParameterScalesFromPhysicalShift.h"
#include "itkCommand.h"
#include <fstream>
template<typename TFilter>
class itkJensenHavrdaCharvatTsallisPointSetMetricRegistrationTestCommandIterationUpdate : public itk::Command
{
public:
typedef itkJensenHavrdaCharvatTsallisPointSetMetricRegistrationTestCommandIterationUpdate Self;
typedef itk::Command Superclass;
typedef itk::SmartPointer<Self> Pointer;
itkNewMacro( Self );
protected:
itkJensenHavrdaCharvatTsallisPointSetMetricRegistrationTestCommandIterationUpdate() {};
public:
virtual void Execute(itk::Object *caller, const itk::EventObject & event) ITK_OVERRIDE
{
Execute( (const itk::Object *) caller, event);
}
virtual void Execute(const itk::Object * object, const itk::EventObject & event) ITK_OVERRIDE
{
if( typeid( event ) != typeid( itk::IterationEvent ) )
{
return;
}
const TFilter *optimizer = dynamic_cast< const TFilter * >( object );
if( !optimizer )
{
itkGenericExceptionMacro( "Error dynamic_cast failed" );
}
std::cout << "It: " << optimizer->GetCurrentIteration() << " metric value: " << optimizer->GetCurrentMetricValue();
std::cout << std::endl;
}
};
int itkJensenHavrdaCharvatTsallisPointSetMetricRegistrationTest( int argc, char *argv[] )
{
const unsigned int Dimension = 2;
unsigned int numberOfIterations = 10;
if( argc > 1 )
{
numberOfIterations = atoi( argv[1] );
}
typedef itk::PointSet<unsigned char, Dimension> PointSetType;
typedef PointSetType::PointType PointType;
PointSetType::Pointer fixedPoints = PointSetType::New();
fixedPoints->Initialize();
PointSetType::Pointer movingPoints = PointSetType::New();
movingPoints->Initialize();
// two ellipses, one rotated slightly
/*
// Having trouble with these, as soon as there's a slight rotation added.
unsigned long count = 0;
for( float theta = 0; theta < 2.0 * itk::Math::pi; theta += 0.1 )
{
float radius = 100.0;
PointType fixedPoint;
fixedPoint[0] = 2 * radius * std::cos( theta );
fixedPoint[1] = radius * std::sin( theta );
fixedPoints->SetPoint( count, fixedPoint );
PointType movingPoint;
movingPoint[0] = 2 * radius * std::cos( theta + (0.02 * itk::Math::pi) ) + 2.0;
movingPoint[1] = radius * std::sin( theta + (0.02 * itk::Math::pi) ) + 2.0;
movingPoints->SetPoint( count, movingPoint );
count++;
}
*/
// two circles with a small offset
PointType offset;
for( unsigned int d=0; d < Dimension; d++ )
{
offset[d] = 2.0;
}
unsigned long count = 0;
for( float theta = 0; theta < 2.0 * itk::Math::pi; theta += 0.1 )
{
PointType fixedPoint;
float radius = 100.0;
fixedPoint[0] = radius * std::cos( theta );
fixedPoint[1] = radius * std::sin( theta );
if( Dimension > 2 )
{
fixedPoint[2] = radius * std::sin( theta );
}
fixedPoints->SetPoint( count, fixedPoint );
PointType movingPoint;
movingPoint[0] = fixedPoint[0] + offset[0];
movingPoint[1] = fixedPoint[1] + offset[1];
if( Dimension > 2 )
{
movingPoint[2] = fixedPoint[2] + offset[2];
}
movingPoints->SetPoint( count, movingPoint );
count++;
}
typedef itk::AffineTransform<double, Dimension> AffineTransformType;
AffineTransformType::Pointer transform = AffineTransformType::New();
transform->SetIdentity();
// Instantiate the metric
typedef itk::JensenHavrdaCharvatTsallisPointSetToPointSetMetricv4<PointSetType> PointSetMetricType;
PointSetMetricType::Pointer metric = PointSetMetricType::New();
metric->SetFixedPointSet( fixedPoints );
metric->SetMovingPointSet( movingPoints );
metric->SetPointSetSigma( 1.0 );
metric->SetKernelSigma( 10.0 );
metric->SetUseAnisotropicCovariances( false );
metric->SetCovarianceKNeighborhood( 5 );
metric->SetEvaluationKNeighborhood( 10 );
metric->SetMovingTransform( transform );
metric->SetAlpha( 1.1 );
metric->Initialize();
// scales estimator
typedef itk::RegistrationParameterScalesFromPhysicalShift< PointSetMetricType > RegistrationParameterScalesFromShiftType;
RegistrationParameterScalesFromShiftType::Pointer shiftScaleEstimator = RegistrationParameterScalesFromShiftType::New();
shiftScaleEstimator->SetMetric( metric );
// needed with pointset metrics
shiftScaleEstimator->SetVirtualDomainPointSet( metric->GetVirtualTransformedPointSet() );
// optimizer
typedef itk::GradientDescentOptimizerv4 OptimizerType;
OptimizerType::Pointer optimizer = OptimizerType::New();
optimizer->SetMetric( metric );
optimizer->SetNumberOfIterations( numberOfIterations );
optimizer->SetScalesEstimator( shiftScaleEstimator );
optimizer->SetMaximumStepSizeInPhysicalUnits( 3.0 );
typedef itkJensenHavrdaCharvatTsallisPointSetMetricRegistrationTestCommandIterationUpdate<OptimizerType> CommandType;
CommandType::Pointer observer = CommandType::New();
optimizer->AddObserver( itk::IterationEvent(), observer );
optimizer->SetMinimumConvergenceValue( 0.0 );
optimizer->SetConvergenceWindowSize( 10 );
optimizer->StartOptimization();
std::cout << "numberOfIterations: " << numberOfIterations << std::endl;
std::cout << "Moving-source final value: " << optimizer->GetCurrentMetricValue() << std::endl;
std::cout << "Moving-source final position: " << optimizer->GetCurrentPosition() << std::endl;
std::cout << "Optimizer scales: " << optimizer->GetScales() << std::endl;
std::cout << "Optimizer learning rate: " << optimizer->GetLearningRate() << std::endl;
// applying the resultant transform to moving points and verify result
std::cout << "Fixed\tMoving\tMovingTransformed\tFixedTransformed\tDiff" << std::endl;
bool passed = true;
PointType::ValueType tolerance = 1e-2;
AffineTransformType::InverseTransformBasePointer movingInverse = metric->GetMovingTransform()->GetInverseTransform();
AffineTransformType::InverseTransformBasePointer fixedInverse = metric->GetFixedTransform()->GetInverseTransform();
for( unsigned int n=0; n < metric->GetNumberOfComponents(); n++ )
{
// compare the points in virtual domain
PointType transformedMovingPoint = movingInverse->TransformPoint( movingPoints->GetPoint( n ) );
PointType transformedFixedPoint = fixedInverse->TransformPoint( fixedPoints->GetPoint( n ) );
PointType difference;
difference[0] = transformedMovingPoint[0] - transformedFixedPoint[0];
difference[1] = transformedMovingPoint[1] - transformedFixedPoint[1];
std::cout << fixedPoints->GetPoint( n ) << "\t" << movingPoints->GetPoint( n )
<< "\t" << transformedMovingPoint << "\t" << transformedFixedPoint << "\t" << difference << std::endl;
if( fabs( difference[0] ) > tolerance || fabs( difference[1] ) > tolerance )
{
passed = false;
}
}
if( ! passed )
{
std::cerr << "Results do not match truth within tolerance." << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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