/usr/include/ITK-4.5/itkCompareHistogramImageToImageMetric.hxx is in libinsighttoolkit4-dev 4.5.0-3.
This file is owned by root:root, with mode 0o644.
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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.
*
*=========================================================================*/
#ifndef __itkCompareHistogramImageToImageMetric_hxx
#define __itkCompareHistogramImageToImageMetric_hxx
#include "itkCompareHistogramImageToImageMetric.h"
#include "itkHistogram.h"
namespace itk
{
template< typename TFixedImage, typename TMovingImage >
CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >::CompareHistogramImageToImageMetric()
{
m_TrainingFixedImage = 0; // has to be provided by the user.
m_TrainingMovingImage = 0; // has to be provided by the user.
m_TrainingTransform = 0; // has to be provided by the user.
m_TrainingInterpolator = 0; // has to be provided by the user.
m_TrainingHistogram = 0; // either provided by the user or created
}
template< typename TFixedImage, typename TMovingImage >
void
CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >
::Initialize()
throw ( ExceptionObject )
{
Superclass::Initialize();
if ( !m_TrainingHistogram )
{
FormTrainingHistogram();
}
}
template< typename TFixedImage, typename TMovingImage >
void
CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >
::FormTrainingHistogram()
throw ( ExceptionObject )
{
// Check to make sure everything is set
if ( !m_TrainingTransform )
{
itkExceptionMacro(<< "Training Transform is not present");
}
if ( !m_TrainingInterpolator )
{
itkExceptionMacro(<< "Training Interpolator is not present");
}
if ( !m_TrainingMovingImage )
{
itkExceptionMacro(<< "Training MovingImage is not present");
}
// If the image is provided by a source, update the source.
if ( m_TrainingMovingImage->GetSource() )
{
m_TrainingMovingImage->GetSource()->Update();
}
if ( !m_TrainingFixedImage )
{
itkExceptionMacro(<< "Training FixedImage is not present");
}
// If the image is provided by a source, update the source.
if ( m_TrainingFixedImage->GetSource() )
{
m_TrainingFixedImage->GetSource()->Update();
}
if ( m_TrainingFixedImageRegion.GetNumberOfPixels() == 0 )
{
itkExceptionMacro(<< "TrainingFixedImageRegion is empty");
}
// Make sure the FixedImageRegion is within the FixedImage buffered region
if ( !m_TrainingFixedImageRegion.Crop( m_TrainingFixedImage->GetBufferedRegion() ) )
{
itkExceptionMacro(<< "TrainingFixedImageRegion does not overlap the training fixed image buffered region");
}
this->m_TrainingInterpolator->SetInputImage( GetTrainingMovingImage() );
// Create the exact histogram structure as the one to be used
// to evaluate the metric. This code is mostly copied
// from itkHistogramImageToImageMetric
this->m_TrainingHistogram = HistogramType::New();
this->m_TrainingHistogram->SetMeasurementVectorSize(2);
this->m_TrainingHistogram->Initialize(this->Superclass::m_HistogramSize,
this->Superclass::m_LowerBound,
this->Superclass::m_UpperBound);
typedef itk::ImageRegionConstIteratorWithIndex< FixedImageType >
TrainingFixedIteratorType;
typename FixedImageType::IndexType index;
typename FixedImageType::RegionType fixedRegion;
TrainingFixedIteratorType ti(this->m_TrainingFixedImage,
this->m_TrainingFixedImageRegion);
int NumberOfPixelsCounted = 0;
ti.GoToBegin();
while ( !ti.IsAtEnd() )
{
index = ti.GetIndex();
if ( this->m_TrainingFixedImageRegion.IsInside(index)
&& ( !this->Superclass::GetUsePaddingValue()
|| ( this->Superclass::GetUsePaddingValue()
&& ti.Get() > this->Superclass::GetPaddingValue() ) ) )
{
typename Superclass::InputPointType inputPoint;
this->m_TrainingFixedImage->
TransformIndexToPhysicalPoint(index, inputPoint);
typename Superclass::OutputPointType transformedPoint =
this->m_TrainingTransform->TransformPoint(inputPoint);
if ( this->m_TrainingInterpolator->IsInsideBuffer(transformedPoint) )
{
const RealType TrainingMovingValue =
this->m_TrainingInterpolator->Evaluate(transformedPoint);
const RealType TrainingFixedValue = ti.Get();
NumberOfPixelsCounted++;
typename HistogramType::MeasurementVectorType sample;
sample.SetSize(2);
sample[0] = TrainingFixedValue;
sample[1] = TrainingMovingValue;
this->m_TrainingHistogram->IncreaseFrequencyOfMeasurement(sample, 1);
}
}
++ti;
}
if ( NumberOfPixelsCounted == 0 )
{
itkExceptionMacro(<< "All the points mapped to outside of the Training moving \
age");
}
}
template< typename TFixedImage, typename TMovingImage >
void CompareHistogramImageToImageMetric< TFixedImage, TMovingImage >::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "TrainingFixedImage: ";
if ( m_TrainingFixedImage.IsNull() )
{
os << 0 << std::endl;
}
else
{
os << m_TrainingFixedImage << std::endl;
}
os << indent << "TrainingMovingImage: ";
if ( m_TrainingMovingImage.IsNull() )
{
os << 0 << std::endl;
}
else
{
os << m_TrainingMovingImage << std::endl;
}
os << indent << "TrainingTransform: ";
if ( m_TrainingTransform.IsNull() )
{
os << 0 << std::endl;
}
else
{
os << m_TrainingTransform << std::endl;
}
os << indent << "TrainingInterpolator: ";
if ( m_TrainingInterpolator.IsNull() )
{
os << 0 << std::endl;
}
else
{
os << m_TrainingInterpolator << std::endl;
}
os << indent << "TrainingHistogram: ";
if ( m_TrainingHistogram.IsNull() )
{
os << 0 << std::endl;
}
else
{
os << m_TrainingHistogram << std::endl;
}
os << indent << "TrainingFixedImageRegion: " << m_TrainingFixedImageRegion
<< std::endl;
}
} // End namespace itk
#endif // itkCompareHistogramImageToImageMetric_hxx
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