/*========================================================================= * * 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 itkExpectationBasedPointSetToPointSetMetricv4_h #define itkExpectationBasedPointSetToPointSetMetricv4_h #include "itkPointSetToPointSetMetricv4.h" #include "itkPointSet.h" #include "itkImage.h" namespace itk { /** * \class ExpectationBasedPointSetToPointSetMetricv4 * \brief Computes an expectation-based metric between two point sets. * * This information-theoretic point set measure models each point set * as a sum of Gaussians. To speed up computation, evaluation of the local * value/derivative is done in a user-specified neighborhood using the k-d * tree constructed in the superclass. * * Reference: * Pluta J, Avants BB, Glynn S, Awate S, Gee JC, Detre JA, * "Appearance and incomplete label matching for diffeomorphic template * "based hippocampus segmentation", Hippocampus, 2009 Jun; 19(6):565-71. * * \ingroup ITKMetricsv4 */ template class ITK_TEMPLATE_EXPORT ExpectationBasedPointSetToPointSetMetricv4 : public PointSetToPointSetMetricv4 { public: ITK_DISALLOW_COPY_AND_MOVE(ExpectationBasedPointSetToPointSetMetricv4); /** Standard class type aliases. */ using Self = ExpectationBasedPointSetToPointSetMetricv4; using Superclass = PointSetToPointSetMetricv4; using Pointer = SmartPointer; using ConstPointer = SmartPointer; /** Method for creation through the object factory. */ itkSimpleNewMacro(Self); /** \see LightObject::GetNameOfClass() */ itkOverrideGetNameOfClassMacro(ExpectationBasedPointSetToPointSetMetricv4); /** Types transferred from the base class */ using typename Superclass::MeasureType; using typename Superclass::DerivativeType; using typename Superclass::LocalDerivativeType; using typename Superclass::PointType; using typename Superclass::PixelType; using typename Superclass::CoordRepType; using typename Superclass::PointIdentifier; using typename Superclass::NeighborsIdentifierType; /** * Calculates the local metric value for a single point. */ MeasureType GetLocalNeighborhoodValue(const PointType &, const PixelType & pixel = 0) const override; /** * Calculates the local value and derivative for a single point. */ void GetLocalNeighborhoodValueAndDerivative(const PointType &, MeasureType &, LocalDerivativeType &, const PixelType & pixel = 0) const override; /** * Each point is associated with a Gaussian characterized by m_PointSetSigma * which provides a sense of scale for determining the similarity between two * point sets. Default = 1.0. */ itkSetMacro(PointSetSigma, CoordRepType); /** Get the point set sigma function */ itkGetConstMacro(PointSetSigma, CoordRepType); /** * Set the neighborhood size used to evaluate the measurement at each * point. Default = 50. */ itkSetMacro(EvaluationKNeighborhood, unsigned int); /** * Get the neighborhood size used to evaluate the measurement at each * point. Default = 50. */ itkGetConstMacro(EvaluationKNeighborhood, unsigned int); void Initialize() override; /** Clone method will clone the existing instance of this type, * including its internal member variables. */ typename LightObject::Pointer InternalClone() const override; protected: ExpectationBasedPointSetToPointSetMetricv4(); ~ExpectationBasedPointSetToPointSetMetricv4() override = default; bool RequiresFixedPointsLocator() const override { return false; } /** PrintSelf function */ void PrintSelf(std::ostream & os, Indent indent) const override; private: using VectorType = typename PointType::VectorType; using NeighborsIterator = typename NeighborsIdentifierType::const_iterator; CoordRepType m_PointSetSigma{}; MeasureType m_PreFactor{}; MeasureType m_Denominator{}; unsigned int m_EvaluationKNeighborhood{ 50 }; }; } // end namespace itk #ifndef ITK_MANUAL_INSTANTIATION # include "itkExpectationBasedPointSetToPointSetMetricv4.hxx" #endif #endif