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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 itkMultiphaseFiniteDifferenceImageFilter_h
#define itkMultiphaseFiniteDifferenceImageFilter_h
#include "itkInPlaceImageFilter.h"
#include "itkFiniteDifferenceFunction.h"
#include "vnl/vnl_vector.h"
#include "itkImageRegionIterator.h"
#include "itkListSample.h"
#include "itkKdTreeGenerator.h"
namespace itk
{
/**
* \class MultiphaseFiniteDifferenceImageFilter
*
* \par The Finite Difference Solver Hierarchy
*
* This is an alternate version of the ITK finite difference solver (FDS)
* framework, supporting the solution of multiple functions, simultaneously.
* The FDS framework is a set of classes for creating filters to solve partial
* differential equations on images using an iterative, finite difference
* update scheme.
*
* \par
* The high-level algorithm implemented by the framework can be described by
* the following pseudocode.
*
* \code
* WHILE NOT convergence:
* FOR ALL pixels i
* FOR ALL functions f
* min_time_step = min(min_time_step, calculate_change(f, i))
* FOR ALL functions f
* update(f, i, time_step)
* \endcode
*
* \par
* The following equation describes update \f$n+1\f$ at pixel \f$i\f$ on
* discrete image \f$ u \f$ :
*
* \par
* \f$u_{\mathbf{i}}^{n+1}=u^n_{\mathbf{i}}+\Delta u^n_{\mathbf{i}}\Delta t\f$
*
* \par Component objects
* The FDS hierarchy is comprised of two component object types, variations of
* which are designed to be plugged together to create filters for different
* applications. At the process level are the ``solver'' objects, which are
* subclasses of MultiphaseFiniteDifferenceImageFilter. Solver objects are filters that
* take image inputs and produce image outputs. Solver objects require a
* ``finite difference function'' object to perform the calculation at each
* image pixel during iteration. These specialized function objects are
* subclasses of FiniteDifferenceFunction. FiniteDifferenceFunctions take a
* neighborhood of pixels as input (in the form of an
* itk::NeighborhoodIterator) and produce a scalar valued result.
*
* \par
* Filters for different applications are created by defining a function object
* to handle the numerical calculations and choosing (or creating) a solver
* object that reflects the requirements and constraints of the application.
* For example, anisotropic diffusion filters are created by plugging
* anisotropic diffusion functions into the DenseFiniteDifferenceImageFilter2.
* The separation between function object and solver object allows us to
* create, for example, sparse-field, dense-field, and narrow-band
* implementations of a level-set surface evolution filter can all be
* constructed by plugging the same function object into three different,
* specialized solvers.
*
* \par Creating new filters in this hierarchy
* The procedure for creating a filter within the FDS hierarchy is to identify
* all the virtual methods that need to be defined for your particular
* application. In the simplest case, a filter needs only to instantiate a
* specific function object and define some halting criteria. For more
* complicated applications, you may need to define a specialized type of
* iteration scheme or updating procedure in a higher-level solver object.
*
* \par
* Some simple examples are the specific subclasses of
* AnisotropicDiffusionImageFilter. The leaves of the anisotropic diffusion
* filter tree only define the function object they use for their particular
* flavor of diffusion. See CurvatureAnisotropicDiffusionImageFilter and
* GradientAnisotropicDiffusionImageFilter for details.
*
* \par FiniteDifferenceImageFilter2
* This class defines the generic solver API at the top level of the FDS
* framework. FiniteDifferenceImageFilter2 is an abstract class that implements
* the generic, high-level algorithm (described above).
*
* \par Inputs and Outputs
* This filter is an Image to Image filter. Depending on the specific
* subclass implementation, finite difference image filters may process a
* variety of image types. The input to the filter is the initial
* value of \f$ u \f$ and the output of the filter is the solution to the
* p.d.e.
*
* \par How to use this class
* GenerateData() relies on several virtual methods that must be defined by a
* subclass. Specifically: \em AllocateUpdateBuffer \em ApplyUpdate
* \em CalculateChange and \em Halt. To create a finite difference solver,
* implement a subclass to define these methods.
*
* \par
* Note that there is no fixed container type for the buffer used to hold the
* update \f$ \Delta \f$. The container might be another image, or simply a
* list of values. AllocateUpdateBuffer is responsible for creating the \f$
* \Delta \f$ container. CalculateChange populates this buffer and ApplyUpdate
* adds the buffer values to the output image (solution). The boolean Halt()
* (or ThreadedHalt) method returns a true value to stop iteration.
*
*
* Based on the paper:
*
* "An active contour model without edges"
* T. Chan and L. Vese.
* In Scale-Space Theories in Computer Vision, pages 141-151, 1999.
*
* \author Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
*
* This code was taken from the Insight Journal paper:
*
* "Cell Tracking using Coupled Active Surfaces for Nuclei and Membranes"
* http://www.insight-journal.org/browse/publication/642
* https://hdl.handle.net/10380/3055
*
* That is based on the papers:
*
* "Level Set Segmentation: Active Contours without edge"
* http://www.insight-journal.org/browse/publication/322
* https://hdl.handle.net/1926/1532
*
* and
*
* "Level set segmentation using coupled active surfaces"
* http://www.insight-journal.org/browse/publication/323
* https://hdl.handle.net/1926/1533
*
*
* \ingroup ImageFilter
* \ingroup LevelSetSegmentation
* \sa DenseFiniteDifferenceImageFilter2
* \ingroup ITKReview
*/
template< typename TInputImage,
typename TFeatureImage,
typename TOutputImage,
typename TFiniteDifferenceFunction = FiniteDifferenceFunction< TOutputImage >,
typename TIdCell = unsigned int >
class MultiphaseFiniteDifferenceImageFilter:
public InPlaceImageFilter< TFeatureImage, TOutputImage >
{
public:
/** Standard class typedefs. */
typedef MultiphaseFiniteDifferenceImageFilter Self;
typedef InPlaceImageFilter< TFeatureImage, TOutputImage > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Run-time type information (and related methods) */
itkTypeMacro(MultiphaseFiniteDifferenceImageFilter, InPlaceImageFilter);
/** Dimensionality of input and output data is assumed to be the same. */
itkStaticConstMacro(ImageDimension, unsigned int, TOutputImage::ImageDimension);
/** Input and output image types. */
typedef TInputImage InputImageType;
typedef typename InputImageType::Pointer InputImagePointer;
typedef typename InputImageType::PointType InputPointType;
typedef typename InputPointType::CoordRepType InputCoordRepType;
typedef typename InputImageType::IndexType InputIndexType;
typedef typename InputIndexType::IndexValueType InputIndexValueType;
typedef typename InputImageType::SizeType InputSizeType;
typedef typename InputSizeType::SizeValueType InputSizeValueType;
typedef typename InputImageType::RegionType InputRegionType;
typedef typename InputImageType::PixelType InputPixelType;
typedef typename InputImageType::SpacingType InputSpacingType;
typedef typename InputImageType::OffsetValueType InputOffsetValueType;
typedef TFeatureImage FeatureImageType;
typedef typename FeatureImageType::Pointer FeatureImagePointer;
typedef typename FeatureImageType::RegionType FeatureRegionType;
typedef typename FeatureImageType::SizeType FeatureSizeType;
typedef typename FeatureImageType::SpacingType FeatureSpacingType;
typedef typename FeatureImageType::PointType FeaturePointType;
typedef typename FeatureImageType::PixelType FeaturePixelType;
typedef TOutputImage OutputImageType;
typedef typename OutputImageType::Pointer OutputImagePointer;
typedef typename OutputImageType::PixelType OutputPixelType;
typedef typename OutputImageType::RegionType OutputRegionType;
typedef typename OutputImageType::SizeType OutputSizeType;
typedef typename OutputImageType::SizeValueType OutputSizeValueType;
typedef typename OutputImageType::IndexType OutputIndexType;
typedef typename OutputImageType::IndexValueType OutputIndexValueType;
typedef TIdCell IdCellType;
typedef std::vector< IdCellType > VectorIdCellType;
/** The value type of the time step. This is distinct from PixelType
* because PixelType may often be a vector value, while the TimeStep is
* a scalar value. */
typedef TFiniteDifferenceFunction FiniteDifferenceFunctionType;
typedef typename FiniteDifferenceFunctionType::Pointer FiniteDifferenceFunctionPointer;
typedef typename FiniteDifferenceFunctionType::TimeStepType TimeStepType;
typedef typename std::vector< TimeStepType > TimeStepVectorType;
typedef typename FiniteDifferenceFunctionType::RadiusType RadiusType;
typedef Vector< float, itkGetStaticConstMacro(ImageDimension) >
CentroidVectorType;
typedef Statistics::ListSample< CentroidVectorType > SampleType;
typedef Statistics::KdTreeGenerator< SampleType > KdTreeGeneratorType;
typedef typename KdTreeGeneratorType::Pointer KdTreeGeneratorPointer;
typedef typename KdTreeGeneratorType::KdTreeType KdTreeType;
typedef typename KdTreeType::Pointer KdTreePointer;
/** This method returns a pointer to a FiniteDifferenceFunction object that
* will be used by the filter to calculate updates at image pixels.
* \param functionIndex Index of difference function to return.
* \returns A FiniteDifferenceObject pointer. */
virtual const FiniteDifferenceFunctionPointer GetDifferenceFunction(
const IdCellType & functionIndex) const
{
if ( functionIndex < m_FunctionCount )
{
return ( this->m_DifferenceFunctions[functionIndex] );
}
else
{
return ITK_NULLPTR;
}
}
/** This method sets the pointer to a FiniteDifferenceFunction object that
* will be used by the filter to calculate updates at image pixels.
* \param functionIndex Index of difference function to set.
* \param function Pointer to difference function to set. */
virtual void SetDifferenceFunction(const IdCellType & functionIndex,
FiniteDifferenceFunctionPointer function)
{
if ( functionIndex < m_FunctionCount )
{
this->m_DifferenceFunctions[functionIndex] = function;
}
}
/** Set/Get the number of iterations that the filter will run. */
itkSetMacro(NumberOfIterations, unsigned int);
itkGetConstReferenceMacro(NumberOfIterations, unsigned int);
/** Use the image spacing information in calculations. Use this option if you
* want derivatives in physical space. Default is UseImageSpacingOn. */
itkSetMacro(UseImageSpacing, bool);
itkBooleanMacro(UseImageSpacing);
itkGetConstReferenceMacro(UseImageSpacing, bool);
/** Set/Get the maximum error allowed in the solution. This may not be
* defined for all solvers and its meaning may change with the application. */
itkSetMacro(MaximumRMSError, double);
itkGetConstReferenceMacro(MaximumRMSError, double);
/** Set/Get the root mean squared change of the previous iteration. May not
be used by all solvers. */
itkSetMacro(RMSChange, double);
itkGetConstReferenceMacro(RMSChange, double);
/** Set/Get the state of the filter. */
itkSetMacro(InitializedState, bool);
itkGetConstReferenceMacro(InitializedState, bool);
itkBooleanMacro(InitializedState);
/** Require the filter to be manually reinitialized (by calling
SetInitializedStateOff() */
itkSetMacro(ManualReinitialization, bool);
itkGetConstReferenceMacro(ManualReinitialization, bool);
itkBooleanMacro(ManualReinitialization);
/** Set the number of elapsed iterations of the filter. */
itkSetMacro(ElapsedIterations, unsigned int);
/** Get the number of elapsed iterations of the filter. */
itkGetConstReferenceMacro(ElapsedIterations, unsigned int);
void SetLevelSet(const IdCellType & i, const InputImageType *levelSet)
{
m_LevelSet[i] = InputImageType::New();
m_LevelSet[i]->SetRequestedRegion( levelSet->GetRequestedRegion() );
m_LevelSet[i]->SetBufferedRegion( levelSet->GetBufferedRegion() );
m_LevelSet[i]->SetLargestPossibleRegion( levelSet->GetLargestPossibleRegion() );
m_LevelSet[i]->Allocate();
m_LevelSet[i]->CopyInformation(levelSet);
ImageRegionConstIterator< InputImageType > in ( levelSet, levelSet->GetBufferedRegion() );
ImageRegionIterator< InputImageType > cp ( m_LevelSet[i], levelSet->GetBufferedRegion() );
in.GoToBegin();
cp.GoToBegin();
while ( !in.IsAtEnd() )
{
cp.Set( in.Get() );
++in;
++cp;
}
}
InputImagePointer GetLevelSet(const IdCellType & i)
{
if ( i >= m_FunctionCount )
{
itkExceptionMacro("Request for level set #" << i
<< " but there are only " << m_FunctionCount);
}
else
{
return m_LevelSet[i];
}
}
void SetLookup(VectorIdCellType lookup)
{
this->m_Lookup = lookup;
}
void SetKdTree(KdTreeType *kdtree)
{
this->m_KdTree = kdtree;
}
void SetFunctionCount(const IdCellType & n)
{
m_FunctionCount = n;
m_DifferenceFunctions.resize(m_FunctionCount, ITK_NULLPTR);
RadiusType radius;
radius.Fill(1);
for ( unsigned int i = 0; i < this->m_FunctionCount; i++ )
{
this->m_DifferenceFunctions[i] = FiniteDifferenceFunctionType::New();
this->m_DifferenceFunctions[i]->Initialize(radius);
}
// Initialize the images
m_LevelSet.resize(m_FunctionCount, ITK_NULLPTR);
// Initialize the lookup table
this->m_Lookup.resize(m_FunctionCount);
IdCellType k = 1;
typedef typename std::vector< IdCellType >::iterator VectorIteratorType;
VectorIteratorType it = this->m_Lookup.begin();
while ( it != this->m_Lookup.end() )
{
*it = k;
++it;
++k;
}
}
protected:
MultiphaseFiniteDifferenceImageFilter()
{
this->m_KdTree = ITK_NULLPTR;
this->m_ElapsedIterations = 0;
this->m_MaximumRMSError = itk::Math::eps;
this->m_RMSChange = NumericTraits< double >::max();
this->m_UseImageSpacing = true;
this->m_ManualReinitialization = false;
this->m_InitializedState = false;
this->m_NumberOfIterations = NumericTraits< unsigned int >::max();
this->m_FunctionCount = 0;
this->InPlaceOff();
}
~MultiphaseFiniteDifferenceImageFilter(){}
IdCellType m_FunctionCount;
std::vector< InputImagePointer > m_LevelSet;
VectorIdCellType m_Lookup;
KdTreePointer m_KdTree;
unsigned int m_ElapsedIterations;
double m_MaximumRMSError;
double m_RMSChange;
unsigned int m_NumberOfIterations;
/** The function that will be used in calculating updates for each pixel. */
std::vector< FiniteDifferenceFunctionPointer > m_DifferenceFunctions;
/** Control whether derivatives use spacing of the input image in its
* calculation. */
bool m_UseImageSpacing;
void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** This method allocates a temporary update container in the subclass. */
virtual void AllocateUpdateBuffer() = 0;
/** This method is defined by a subclass to apply changes to the output
* from an update buffer and a time step value "dt".
* \param dt Time step value. */
virtual void ApplyUpdate(TimeStepType dt) = 0;
/** This method is defined by a subclass to populate an update buffer
* with changes for the pixels in the output. It returns a time
* step value to be used for the update.
* \returns A time step to use in updating the output with the changes
* calculated from this method. */
virtual TimeStepType CalculateChange() = 0;
/** This method can be defined in subclasses as needed to copy the input
* to the output. See DenseFiniteDifferenceImageFilter2 for an
* implementation. */
virtual void CopyInputToOutput() = 0;
/** This is the default, high-level algorithm for calculating finite
* difference solutions. It calls virtual methods in its subclasses
* to implement the major steps of the algorithm. */
virtual void GenerateData() ITK_OVERRIDE;
/** FiniteDifferenceImageFilter2 needs a larger input requested region than
* the output requested region. As such, we need to provide
* an implementation for GenerateInputRequestedRegion() in order to inform
* the pipeline execution model.
*
* \par
* The filter will ask for a padded region to perform its neighborhood
* calculations. If no such region is available, the boundaries will be
* handled as described in the FiniteDifferenceFunction defined by the
* subclass.
* \sa ProcessObject::GenerateInputRequestedRegion() */
virtual void GenerateInputRequestedRegion() ITK_OVERRIDE;
/** This method returns true when the current iterative solution of the
* equation has met the criteria to stop solving. Defined by a subclass. */
virtual bool Halt();
/** This method is similar to Halt(), and its default implementation in this
* class is simply to call Halt(). However, this method takes as a parameter a
* void pointer to the MultiThreader::ThreadInfoStruct structure. If you
* override this method instead of overriding Halt, you will be able to get the
* current thread ID and handle the Halt method accordingly. This is useful if
* you are doing a lot of processing in Halt that you don't want parallelized.
* Notice that ThreadedHalt is only called by the multithreaded filters, so you
* still should implement Halt, just in case a non-threaded filter is used.
*/
virtual bool ThreadedHalt( void *itkNotUsed(threadInfo) )
{
return this->Halt();
}
/** This method is optionally defined by a subclass and is called before
* the loop of iterations of calculate_change & upate. It does the global
* initialization, i.e. in the SparseFieldLevelSetImageFilter, initialize
* the list of layers.
* */
virtual void Initialize() {}
/** This method is optionally defined by a subclass and is called immediately
* prior to each iterative CalculateChange-ApplyUpdate cycle. It can be
* used to set global variables needed for the next iteration (ie. average
* gradient magnitude of the image in anisotropic diffusion functions), or
* otherwise prepare for the next iteration.
* */
virtual void InitializeIteration()
{
for ( IdCellType i = 0; i < this->m_FunctionCount; i++ )
{
this->m_DifferenceFunctions[i]->InitializeIteration();
}
}
/** Virtual method for resolving a single time step from a set of time steps
* returned from processing threads.
* \return Time step (dt) for the iteration update based on a list
* of time steps generated from the threaded calculated change method (one
* for each region processed).
*
* \param timeStepList The set of time changes compiled from all the threaded
* calls to ThreadedGenerateData.
*
* \param valid The set of flags indicating which of "list" elements are valid
*
* The default is to return the minimum value in the list. */
inline TimeStepType ResolveTimeStep(const TimeStepVectorType & timeStepList,
const std::vector< bool > & valid);
/** This method is called after the solution has been generated to allow
* subclasses to apply some further processing to the output. */
virtual void PostProcessOutput() {}
private:
MultiphaseFiniteDifferenceImageFilter(const Self &) ITK_DELETE_FUNCTION;
void operator=(const Self &) ITK_DELETE_FUNCTION;
/** Indicates whether the filter automatically resets to UNINITIALIZED state
after completing, or whether filter must be manually reset */
bool m_ManualReinitialization;
/** State that the filter is in, i.e. UNINITIALIZED or INITIALIZED */
bool m_InitializedState;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkMultiphaseFiniteDifferenceImageFilter.hxx"
#endif
#endif
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