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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.
*
*=========================================================================*/
// This one header will include all SimpleITK filters and external
// objects.
#include <SimpleITK.h>
#include <iostream>
#include <stdlib.h>
#include <iomanip>
#include <numeric>
namespace sitk = itk::simple;
class IterationUpdate
: public sitk::Command
{
public:
IterationUpdate( const sitk::ImageRegistrationMethod &m)
: m_Method(m)
{}
virtual void Execute( )
{
// use sitk's output operator for std::vector etc..
using sitk::operator<<;
// stash the stream state
std::ios state(NULL);
state.copyfmt(std::cout);
std::cout << std::fixed << std::setfill(' ') << std::setprecision( 5 );
std::cout << std::setw(3) << m_Method.GetOptimizerIteration();
std::cout << " = " << std::setw(7) << m_Method.GetMetricValue();
std::cout << " : " << m_Method.GetOptimizerPosition() << std::endl;
std::cout.copyfmt(state);
}
private:
const sitk::ImageRegistrationMethod &m_Method;
};
int main(int argc, char *argv[])
{
if ( argc < 4 )
{
std::cerr << "Usage: " << argv[0] << " <fixedImageFilter> <movingImageFile> <outputTransformFile>" << std::endl;
return 1;
}
sitk::Image fixed = sitk::ReadImage( argv[1], sitk::sitkFloat32 );
fixed = sitk::Normalize( fixed );
fixed = sitk::DiscreteGaussian( fixed, 2.0 );
sitk::Image moving = sitk::ReadImage( argv[2], sitk::sitkFloat32 );
moving = sitk::Normalize( moving );
moving = sitk::DiscreteGaussian( moving, 2.0);
sitk::ImageRegistrationMethod R;
R.SetMetricAsJointHistogramMutualInformation( );
const double learningRate = 1;
const unsigned int numberOfIterations = 200;
const double convergenceMinimumValue = 1e-4;
const unsigned int convergenceWindowSize=5;
R.SetOptimizerAsGradientDescentLineSearch ( learningRate,
numberOfIterations,
convergenceMinimumValue,
convergenceWindowSize);
R.SetInitialTransform( sitk::TranslationTransform( fixed.GetDimension() ) );
R.SetInterpolator( sitk::sitkLinear );
IterationUpdate cmd(R);
R.AddCommand( sitk::sitkIterationEvent, cmd);
sitk::Transform outTx = R.Execute( fixed, moving );
std::cout << "-------" << std::endl;
std::cout << outTx.ToString() << std::endl;
std::cout << "Optimizer stop condition: " << R.GetOptimizerStopConditionDescription() << std::endl;
std::cout << " Iteration: " << R.GetOptimizerIteration() << std::endl;
std::cout << " Metric value: " << R.GetMetricValue() << std::endl;
sitk::WriteTransform(outTx, argv[3]);
return 0;
}
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