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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 itkANTSNeighborhoodCorrelationImageToImageMetricv4_h
#define itkANTSNeighborhoodCorrelationImageToImageMetricv4_h
#include "itkImageToImageMetricv4.h"
#include "itkANTSNeighborhoodCorrelationImageToImageMetricv4GetValueAndDerivativeThreader.h"
namespace itk {
/** \class ANTSNeighborhoodCorrelationImageToImageMetricv4
*
* \brief Computes normalized cross correlation using a small neighborhood
* for each voxel between two images, with speed optimizations for dense
* registration.
*
* Please cite this reference for more details:
*
* Brian B. Avants, Nicholas J. Tustison, Gang Song, Philip A. Cook,
* Arno Klein, James C. Gee, A reproducible evaluation of ANTs similarity metric
* performance in brain image registration, NeuroImage, Volume 54, Issue 3,
* 1 February 2011, Pages 2033-2044, ISSN 1053-8119,
* DOI: 10.1016/j.neuroimage.2010.09.025.
*
* Around each voxel, the neighborhood is defined as a N-Dimensional
* rectangle centered at the voxel. The size of the rectangle is 2*radius+1.
* The normalized correlation between neighborhoods of fixed image and moving
* image are averaged over the whole image as the final metric.
* \note A radius less than 2 can be unstable. 2 is the default.
*
* This class uses a specific fast implementation that is described in the
* above paper. There are two particular speed-ups:
*
* 1) It is assumed that the derivative is only affected by changes in the
* transform at the center of the window. This is obviously not true but speeds
* the evaluation up considerably and works well in practice. This assumption
* is the main differentiation of this approach from a more generic one.
*
* 2) The evaluation uses on-the-fly queues with multi-threading and a sliding
* neighborhood window. This is described in the above paper and specifically
* optimized for dense registration.
*
* Example of usage:
*
* typedef itk::ANTSNeighborhoodCorrelationImageToImageMetricv4
* <ImageType, ImageType> MetricType;
* typedef MetricType::Pointer MetricTypePointer;
* MetricTypePointer metric = MetricType::New();
*
* // set all parameters
* Size<Dimension> neighborhoodRadius;
* neighborhoodRadius.Fill(2);
* metric->SetRadius(neighborhood_radius);
* metric->SetFixedImage(fixedImage);
* metric->SetMovingImage(movingImage);
* metric->SetFixedTransform(transformFix);
* metric->SetMovingTransform(transformMov);
*
* // initialization after parameters are set.
* metric->Initialize();
*
* // getting derivative and metric value
* metric->GetValueAndDerivative(valueReturn, derivativeReturn);
*
*
* This class is templated over the type of the two input objects.
* This is the base class for a hierarchy of similarity metrics that may, in
* derived classes, operate on meshes, images, etc. This class computes a
* value that measures the similarity between the two objects.
*
* \note Sparse sampling is not supported by this metric. An exception will be
* thrown if m_UseFixedSampledPointSet is set. Support for sparse sampling
* will require a parallel implementation of the neighborhood scanning, which
* currently caches information as the neighborhood window moves.
*
* \ingroup ITKMetricsv4
*/
template<typename TFixedImage, typename TMovingImage, typename TVirtualImage = TFixedImage,
typename TInternalComputationValueType = double,
typename TMetricTraits = DefaultImageToImageMetricTraitsv4<TFixedImage,TMovingImage,TVirtualImage,TInternalComputationValueType>
>
class ITK_TEMPLATE_EXPORT ANTSNeighborhoodCorrelationImageToImageMetricv4 :
public ImageToImageMetricv4<TFixedImage, TMovingImage, TVirtualImage, TInternalComputationValueType, TMetricTraits>
{
public:
/** Standard class typedefs. */
typedef ANTSNeighborhoodCorrelationImageToImageMetricv4 Self;
typedef ImageToImageMetricv4<TFixedImage, TMovingImage, TVirtualImage,
TInternalComputationValueType,TMetricTraits> Superclass;
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
itkTypeMacro(Self, Superclass);
/** superclass types */
typedef typename Superclass::MeasureType MeasureType;
typedef typename Superclass::DerivativeType DerivativeType;
typedef typename Superclass::DerivativeValueType DerivativeValueType;
typedef typename Superclass::VirtualPointType VirtualPointType;
typedef typename Superclass::FixedImagePointType FixedImagePointType;
typedef typename Superclass::FixedImagePixelType FixedImagePixelType;
typedef typename Superclass::FixedTransformType FixedTransformType;
typedef typename Superclass::FixedImageGradientType FixedImageGradientType;
typedef typename FixedTransformType::JacobianType FixedImageJacobianType;
typedef typename Superclass::MovingImagePointType MovingImagePointType;
typedef typename Superclass::MovingImagePixelType MovingImagePixelType;
typedef typename Superclass::MovingImageGradientType MovingImageGradientType;
typedef typename Superclass::MovingTransformType MovingTransformType;
typedef typename MovingTransformType::JacobianType MovingImageJacobianType;
typedef typename Superclass::JacobianType JacobianType;
typedef typename Superclass::VirtualImageGradientType VirtualImageGradientType;
typedef typename Superclass::FixedImageType FixedImageType;
typedef typename Superclass::MovingImageType MovingImageType;
typedef typename Superclass::VirtualImageType VirtualImageType;
typedef typename Superclass::FixedOutputPointType FixedOutputPointType;
typedef typename Superclass::MovingOutputPointType MovingOutputPointType;
typedef typename Superclass::FixedTransformType::JacobianType
FixedTransformJacobianType;
typedef typename Superclass::MovingTransformType::JacobianType
MovingTransformJacobianType;
typedef typename Superclass::NumberOfParametersType NumberOfParametersType;
typedef typename Superclass::ImageDimensionType ImageDimensionType;
typedef typename VirtualImageType::RegionType ImageRegionType;
typedef typename VirtualImageType::SizeType RadiusType;
typedef typename VirtualImageType::IndexType IndexType;
/* Image dimension accessors */
itkStaticConstMacro(FixedImageDimension, ImageDimensionType,
FixedImageType::ImageDimension);
itkStaticConstMacro(MovingImageDimension, ImageDimensionType,
MovingImageType::ImageDimension);
itkStaticConstMacro(VirtualImageDimension, ImageDimensionType,
VirtualImageType::ImageDimension);
// Set the radius of the neighborhood window centered at each pixel.
// See the note above about using a radius less than 2.
itkSetMacro(Radius, RadiusType);
// Get the Radius of the neighborhood window centered at each pixel
itkGetMacro(Radius, RadiusType);
itkGetConstMacro(Radius, RadiusType);
void Initialize(void) ITK_OVERRIDE;
protected:
ANTSNeighborhoodCorrelationImageToImageMetricv4();
virtual ~ANTSNeighborhoodCorrelationImageToImageMetricv4() ITK_OVERRIDE;
friend class ANTSNeighborhoodCorrelationImageToImageMetricv4GetValueAndDerivativeThreader< ThreadedImageRegionPartitioner< VirtualImageDimension >, Superclass, Self >;
typedef ANTSNeighborhoodCorrelationImageToImageMetricv4GetValueAndDerivativeThreader< ThreadedImageRegionPartitioner< VirtualImageDimension >, Superclass, Self >
ANTSNeighborhoodCorrelationImageToImageMetricv4DenseGetValueAndDerivativeThreaderType;
friend class ANTSNeighborhoodCorrelationImageToImageMetricv4GetValueAndDerivativeThreader< ThreadedIndexedContainerPartitioner, Superclass, Self >;
typedef ANTSNeighborhoodCorrelationImageToImageMetricv4GetValueAndDerivativeThreader< ThreadedIndexedContainerPartitioner, Superclass, Self >
ANTSNeighborhoodCorrelationImageToImageMetricv4SparseGetValueAndDerivativeThreaderType;
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(ANTSNeighborhoodCorrelationImageToImageMetricv4);
// Radius of the neighborhood window centered at each pixel
RadiusType m_Radius;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkANTSNeighborhoodCorrelationImageToImageMetricv4.hxx"
#endif
#endif
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