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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 itkDisplacementFieldJacobianDeterminantFilter_h
#define itkDisplacementFieldJacobianDeterminantFilter_h
#include "itkNeighborhoodIterator.h"
#include "itkImageToImageFilter.h"
#include "itkVector.h"
#include "vnl/vnl_matrix.h"
#include "vnl/vnl_det.h"
namespace itk
{
/** \class DisplacementFieldJacobianDeterminantFilter
*
* \brief Computes a scalar image from a vector image (e.g., deformation field)
* input, where each output scalar at each pixel is the Jacobian determinant
* of the vector field at that location. This calculation is correct in the
* case where the vector image is a "displacement" from the current location.
* The computation for the jacobian determinant is: det[ dT/dx ] = det[ I + du/dx ].
*
* \par Overview
* This filter is based on itkVectorGradientMagnitudeImageFilter and supports
* the m_DerivativeWeights weights for partial derivatives.
*
* Note that the determinant of a zero vector field is also zero, whereas
* the Jacobian determinant of the corresponding identity warp transformation
* is 1.0. In order to compute the effective deformation Jacobian determinant
* 1.0 must be added to the diagonal elements of Jacobian prior to taking the derivative.
* i.e. det([ (1.0+dx/dx) dx/dy dx/dz ; dy/dx (1.0+dy/dy) dy/dz; dz/dx dz/dy (1.0+dz/dz) ])
*
* \par Template Parameters (Input and Output)
* This filter has one required template parameter which defines the input
* image type. The pixel type of the input image is assumed to be a vector
* (e.g., itk::Vector, itk::RGBPixel, itk::FixedArray). The scalar type of the
* vector components must be castable to floating point. Instantiating with an
* image of RGBPixel<unsigned short>, for example, is allowed, but the filter
* will convert it to an image of Vector<float,3> for processing.
*
* The second template parameter, TRealType, can be optionally specified to
* define the scalar numerical type used in calculations. This is the
* component type of the output image, which will be of
* itk::Vector<TRealType, N>, where N is the number of channels in the multiple
* component input image. The default type of TRealType is float. For extra
* precision, you may safely change this parameter to double.
*
* The third template parameter is the output image type. The third parameter
* will be automatically constructed from the first and second parameters, so
* it is not necessary (or advisable) to set this parameter explicitly. Given
* an M-channel input image with dimensionality N, and a numerical type
* specified as TRealType, the output image will be of type
* itk::Image<TRealType, N>.
*
* \par Filter Parameters
* The method UseImageSpacingOn will cause derivatives in the image to be
* scaled (inversely) with the pixel size of the input image, effectively
* taking derivatives in world coordinates (versus isotropic image
* space). UseImageSpacingOff turns this functionality off. Default is
* UseImageSpacingOn. The parameter UseImageSpacing can
* be set directly with the method SetUseImageSpacing(bool).
*
* Weights can be applied to the derivatives directly using the
* SetDerivativeWeights method. Note that if UseImageSpacing is set to TRUE
* (ON), then these weights will be overridden by weights derived from the
* image spacing when the filter is updated. The argument to this method is a
* C array of TRealValue type.
*
* \par Constraints
* We use vnl_det for determinant computation, which only supports square
* matrices. So the vector dimension of the input image values must be equal
* to the image dimensions, which is trivially true for a deformation field
* that maps an n-dimensional space onto itself.
* Currently, dimensions up to and including 4 are supported. This
* limitation comes from the presence of vnl_det() functions for matrices of
* dimension up to 4x4.
*
* The template parameter TRealType must be floating point (float or double) or
* a user-defined "real" numerical type with arithmetic operations defined
* sufficient to compute derivatives.
*
* \ingroup GradientFilters
*
* \sa Image
* \sa Neighborhood
* \sa NeighborhoodOperator
* \sa NeighborhoodIterator
*
* \note This class was adapted by
* \author Hans J. Johnson, The University of Iowa
* from code provided by
* \author Tom Vercauteren, INRIA & Mauna Kea Technologies
* \author Torsten Rohlfing, Neuroscience Program, SRI International.
* \ingroup ITKDisplacementField
*/
template <typename TInputImage,
typename TRealType = float,
typename TOutputImage = Image<TRealType, TInputImage::ImageDimension>>
class ITK_TEMPLATE_EXPORT DisplacementFieldJacobianDeterminantFilter
: public ImageToImageFilter<TInputImage, TOutputImage>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(DisplacementFieldJacobianDeterminantFilter);
/** Standard class type aliases. */
using Self = DisplacementFieldJacobianDeterminantFilter;
using Superclass = ImageToImageFilter<TInputImage, TOutputImage>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(DisplacementFieldJacobianDeterminantFilter);
/** Extract some information from the image types. Dimensionality
* of the two images is assumed to be the same. */
using OutputPixelType = typename TOutputImage::PixelType;
using InputPixelType = typename TInputImage::PixelType;
/** Image type alias support */
using InputImageType = TInputImage;
using OutputImageType = TOutputImage;
using InputImagePointer = typename InputImageType::Pointer;
using OutputImagePointer = typename OutputImageType::Pointer;
/** The dimensionality of the input and output images. */
static constexpr unsigned int ImageDimension = TOutputImage::ImageDimension;
/** Length of the vector pixel type of the input image. */
static constexpr unsigned int VectorDimension = InputPixelType::Dimension;
/** Define the data type and the vector of data type used in calculations. */
using RealType = TRealType;
using RealVectorType = Vector<TRealType, InputPixelType::Dimension>;
using RealVectorImageType = Image<RealVectorType, TInputImage::ImageDimension>;
/** Type of the iterator that will be used to move through the image. Also
the type which will be passed to the evaluate function */
using ConstNeighborhoodIteratorType = ConstNeighborhoodIterator<RealVectorImageType>;
using RadiusType = typename ConstNeighborhoodIteratorType::RadiusType;
/** Superclass type alias. */
using typename Superclass::OutputImageRegionType;
/** DisplacementFieldJacobianDeterminantFilter needs a larger input requested
* region than the output requested region (larger by the kernel
* size to calculate derivatives). As such,
* DisplacementFieldJacobianDeterminantFilter needs to provide an
* implementation for GenerateInputRequestedRegion() in order to inform the
* pipeline execution model.
*
* \sa ImageToImageFilter::GenerateInputRequestedRegion() */
void
GenerateInputRequestedRegion() override;
/** Set/Get whether or not the filter will use the spacing of the input
* image (1/spacing) in the calculation of the Jacobian determinant. Use On
* to compute the Jacobian determinant in the space in which the data was
* acquired; use Off to reset the derivative weights, ignore the image
* spacing, and to compute the Jacobian determinant in the image space.
* Default is On. */
void
SetUseImageSpacing(bool);
itkGetConstMacro(UseImageSpacing, bool);
itkBooleanMacro(UseImageSpacing);
#if !defined(ITK_FUTURE_LEGACY_REMOVE)
/** Set the derivative weights according to the spacing of the input image
(1/spacing). Use this option if you want to calculate the Jacobian
determinant in the space in which the data was acquired. Default
is ImageSpacingOn.
\deprecated Use DisplacementFieldJacobianDeterminantFilter::UseImageSpacingOn instead. */
void
SetUseImageSpacingOn()
{
this->SetUseImageSpacing(true);
}
/** Reset the derivative weights to ignore image spacing. Use this option if
you want to calculate the Jacobian determinant in the image space.
Default is ImageSpacingOn.
\deprecated Use DisplacementFieldJacobianDeterminantFilter::UseImageSpacingOff instead. */
void
SetUseImageSpacingOff()
{
this->SetUseImageSpacing(false);
}
#endif
using WeightsType = FixedArray<TRealType, ImageDimension>;
/** Directly Set/Get the array of weights used in the gradient calculations.
Note that calling UseImageSpacingOn will clobber these values. */
void
SetDerivativeWeights(const WeightsType &);
itkGetConstReferenceMacro(DerivativeWeights, WeightsType);
protected:
DisplacementFieldJacobianDeterminantFilter();
~DisplacementFieldJacobianDeterminantFilter() override = default;
/** Do any necessary casting/copying of the input data. Input pixel types
whose value types are not real number types must be cast to real number
types. */
void
BeforeThreadedGenerateData() override;
/** DisplacementFieldJacobianDeterminantFilter can be implemented as a
* multithreaded filter (we're only using vnl_det(), which is trivially
* thread safe). Therefore, this implementation provides a
* DynamicThreadedGenerateData() routine which is called for each
* processing thread. The output image data is allocated
* automatically by the superclass prior to calling
* DynamicThreadedGenerateData(). DynamicThreadedGenerateData can only write to
* the portion of the output image specified by the parameter
* "outputRegionForThread"
*
* \sa ImageToImageFilter::ThreadedGenerateData(),
* ImageToImageFilter::GenerateData() */
void
DynamicThreadedGenerateData(const OutputImageRegionType & outputRegionForThread) override;
void
PrintSelf(std::ostream & os, Indent indent) const override;
using ImageBaseType = typename InputImageType::Superclass;
/** Get access to the input image casted as real pixel values */
itkGetConstObjectMacro(RealValuedInputImage, ImageBaseType);
/** Get/Set the neighborhood radius used for gradient computation */
itkGetConstReferenceMacro(NeighborhoodRadius, RadiusType);
itkSetMacro(NeighborhoodRadius, RadiusType);
virtual TRealType
EvaluateAtNeighborhood(const ConstNeighborhoodIteratorType & it) const;
/** The weights used to scale partial derivatives during processing */
WeightsType m_DerivativeWeights{};
/** Pre-compute 0.5*m_DerivativeWeights since that is the only thing used in
the computations. */
WeightsType m_HalfDerivativeWeights{};
private:
bool m_UseImageSpacing{ true };
ThreadIdType m_RequestedNumberOfWorkUnits{};
typename ImageBaseType::ConstPointer m_RealValuedInputImage{};
RadiusType m_NeighborhoodRadius{};
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkDisplacementFieldJacobianDeterminantFilter.hxx"
#endif
#endif
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