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/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkSimilarityIndexImageFilter_h
#define itkSimilarityIndexImageFilter_h
#include "itkImageToImageFilter.h"
#include "itkNumericTraits.h"
#include "itkArray.h"
namespace itk
{
/**
* \class SimilarityIndexImageFilter
* \brief Measures the similarity between the set of non-zero pixels of
* two images.
*
* SimilarityIndexImageFilter measures the similarity between the set
* non-zero pixels of two images using the following formula:
* \f[ S = \frac{2 | A \cap B |}{|A| + |B|} \f]
* where \f$A\f$ and \f$B\f$ are respectively the set of non-zero pixels
* in the first and second input images. Operator \f$|\cdot|\f$ represents
* the size of a set and \f$\cap\f$ represents the intersection of two sets.
*
* The measure is derived from a reliability measure known as the kappa
* statistic. \f$S\f$ is sensitive to both differences in size and in
* location and have been in the literature for comparing two segmentation masks.
* For more information see:
* "Morphometric Analysis of White Matter Lesions in MR Images: Method and
* Validation", A. P. Zijdenbos, B. M. Dawant, R. A. Margolin and
* A. C. Palmer, IEEE Trans. on Medical Imaging, 13(4) pp 716-724,1994
*
*
* This filter requires the largest possible region of the first image
* and the same corresponding region in the second image.
* It behaves as filter with
* two input and one output. Thus it can be inserted in a pipeline with
* other filters. The filter passes the first input through unmodified.
*
* This filter is templated over the two input image type. It assume
* both image have the same number of dimensions.
*
* \ingroup MultiThreaded
* \ingroup ITKImageCompare
*/
template <typename TInputImage1, typename TInputImage2>
class ITK_TEMPLATE_EXPORT SimilarityIndexImageFilter : public ImageToImageFilter<TInputImage1, TInputImage1>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(SimilarityIndexImageFilter);
/** Standard Self type alias */
using Self = SimilarityIndexImageFilter;
using Superclass = ImageToImageFilter<TInputImage1, TInputImage1>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(SimilarityIndexImageFilter);
/** Image related type alias. */
using InputImage1Type = TInputImage1;
using InputImage2Type = TInputImage2;
using InputImage1Pointer = typename TInputImage1::Pointer;
using InputImage2Pointer = typename TInputImage2::Pointer;
using InputImage1ConstPointer = typename TInputImage1::ConstPointer;
using InputImage2ConstPointer = typename TInputImage2::ConstPointer;
using RegionType = typename TInputImage1::RegionType;
using SizeType = typename TInputImage1::SizeType;
using IndexType = typename TInputImage1::IndexType;
using InputImage1PixelType = typename TInputImage1::PixelType;
using InputImage2PixelType = typename TInputImage2::PixelType;
/** Image related type alias. */
static constexpr unsigned int ImageDimension = TInputImage1::ImageDimension;
/** Type to use form computations. */
using RealType = typename NumericTraits<InputImage1PixelType>::RealType;
/** Set the first input. */
void
SetInput1(const InputImage1Type * image)
{
this->SetInput(image);
}
/** Set the second input. */
void
SetInput2(const InputImage2Type * image);
/** Get the first input. */
const InputImage1Type *
GetInput1()
{
return this->GetInput();
}
/** Get the second input. */
const InputImage2Type *
GetInput2();
/** Return the computed similarity index. */
itkGetConstMacro(SimilarityIndex, RealType);
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro(Input1HasNumericTraitsCheck, (Concept::HasNumericTraits<InputImage1PixelType>));
itkConceptMacro(Input2HasNumericTraitsCheck, (Concept::HasNumericTraits<InputImage2PixelType>));
// End concept checking
#endif
protected:
SimilarityIndexImageFilter();
~SimilarityIndexImageFilter() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
/** Pass the input through unmodified. Do this by Grafting in the
* AllocateOutputs method. */
void
AllocateOutputs() override;
/** Initialize some accumulators before the threads run. */
void
BeforeThreadedGenerateData() override;
/** Do final mean and variance computation from data accumulated in threads.
*/
void
AfterThreadedGenerateData() override;
/** Multi-thread version GenerateData. */
void
ThreadedGenerateData(const RegionType & outputRegionForThread, ThreadIdType threadId) override;
void
DynamicThreadedGenerateData(const RegionType &) override
{
itkExceptionMacro("This class requires threadId so it must use classic multi-threading model");
}
// Override since the filter needs all the data for the algorithm
void
GenerateInputRequestedRegion() override;
// Override since the filter produces all of its output
void
EnlargeOutputRequestedRegion(DataObject * data) override;
private:
RealType m_SimilarityIndex{};
Array<SizeValueType> m_CountOfImage1{};
Array<SizeValueType> m_CountOfImage2{};
Array<SizeValueType> m_CountOfIntersection{};
}; // end of class
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkSimilarityIndexImageFilter.hxx"
#endif
#endif
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