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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 itkNarrowBandLevelSetImageFilter_h
#define itkNarrowBandLevelSetImageFilter_h
#include "itkNarrowBandImageFilterBase.h"
#include "itkSegmentationLevelSetFunction.h"
#include "itkFastChamferDistanceImageFilter.h"
#include "itkIsoContourDistanceImageFilter.h"
#include "itkMath.h"
namespace itk
{
/**
*
* \class NarrowBandLevelSetImageFilter
*
* \brief A base class which defines the API for implementing a special class of
* image segmentation filters using level set methods.
*
* \par OVERVIEW
* This object defines the framework for a class of segmentation filters which
* use level set methods. These filters work by constructing a "feature image"
* onto which the evolving level set locks as it moves. In the feature image,
* values that are close to zero are associated with object boundaries. An
* original (or preprocessed) image is given to the filter as the feature image
* and a seed for the level set is given as the input of the filter. The seed is
* converted into a level set embedding which propagates according to the features
* calculated from the original image.
*
* \par TEMPLATE PARAMETERS
* There are two required and two optional template parameter for these
* filters. Of the optional parameters, the last, TOutputImage, should not be
* changed from its default. It is only there to instantiate the parent class
* correctly.
*
* TInputImage is the image type of the initial model you will input to the
* filter using SetInput() or SetInitialImage().
*
* TFeatureImage is the image type of the image from which the filter will
* calculate the speed term for segmentation (see INPUTS).
*
* TOutputPixelType is the data type used for the output image phi, the implicit
* level set image. This should really only ever be set as float (default) or
* double.
*
* \par INPUTS
* The input to any subclass of this filter is the seed image for the initial
* level set embedding. As with other subclasses of the
* SparseLevelSetImageFilter, the type of the input image is is not important.
* The (RequestedRegion) size of the seed image must, however, match the
* (RequestedRegion) size of the feature image.
*
* You must identify the initial front (surface) in the input image. You do
* this by specifying its isovalue through the method SetIsoSurfaceValue(float
* f). The algorithm will then initialize its solution using the front represented by
* value f. Note that the front is always represented by isosurface zero in
* the output and not the isosurface you specified for the input. This is
* because, for simplicity, the filter will shift your input image so that the
* active front has zero values.
*
* \par
* Depending on the particular application and filter that you are using, the
* feature image should be preprocessed with some type of noise reduction
* filtering. The feature image input can be of any type, but it will be cast
* to floating point before calculations are done.
*
* \par OUTPUTS
* The output of any subclass of this filter is a level set embedding as
* described in SparseFieldLevelSetImageFilter. The zero crossings of the output
* image give the pixels closest to the level set boundary. By ITK convention,
* NEGATIVE values are pixels INSIDE the segmented region and POSITIVE values are
* pixels OUTSIDE the segmented region.
*
* \par PARAMETERS
* The MaximumRMSChange parameter is used to determine when the solution has
* converged. A lower value will result in a tighter-fitting solution, but
* will require more computations. Too low a value could put the solver into
* an infinite loop unless a reasonable NumberOfIterations parameter is set.
* Values should always be greater than 0.0 and less than 1.0.
*
* \par
* The NumberOfIterations parameter can be used to halt the solution after a
* specified number of iterations, overriding the MaximumRMSChange halting
* criteria.
*
* \par
* The standard convention for ITK level-set segmentation filters is that
* POSITIVE propagation (speed) and advection terms cause the surface to EXPAND
* while negative terms cause the surface to CONTRACT. When the
* ReverseExpansionDirection parameter is set to TRUE (on), it tells the
* function object to reverse the standard ITK convention so that NEGATIVE
* terms cause EXPANSION and positive terms cause CONTRACTION.
*
* This parameter can be safely changed as appropriate for a particular
* application or data set to achieve the desired behavior.
*
* \par
* The FeatureScaling parameter controls the magnitude of the features calculated
* for use in the level set propagation and advection speeds. This value simply
* sets both parameters to equal values at once. Some filters may only use on of
* these two terms and this method is a generic way to set either or both without
* having to know which is in use.
*
* \par
* The CurvatureScaling parameter controls the magnitude of the curvature values
* which are calculated on the evolving isophote. This is important in
* controlling the relative effect of curvature in the calculation. Default
* value is 1.0. Higher values relative to the other level set equation terms
* (propagation and advection) will give a smoother result.
*
* \par
* The PropagationScaling parameter controls the scaling of the scalar
* propagation (speed) term relative to other terms in the level set
* equation. Setting this value will override any value already set by
* FeatureScaling.
*
* \par
* The AdvectionScaling parameter controls the scaling of the vector
* advection field term relative to other terms in the level set
* equation. Setting this value will override any value already set by
* FeatureScaling.
*
* \par
* See LevelSetFunction for more information.
* \ingroup ITKLevelSets
*/
template< typename TInputImage,
typename TFeatureImage,
typename TOutputPixelType = float,
typename TOutputImage = Image< TOutputPixelType,
TInputImage::ImageDimension > >
class ITK_TEMPLATE_EXPORT NarrowBandLevelSetImageFilter:
public NarrowBandImageFilterBase< TInputImage, TOutputImage >
{
public:
/** Standard class typedefs */
typedef NarrowBandLevelSetImageFilter Self;
typedef NarrowBandImageFilterBase< TInputImage, TOutputImage > Superclass;
typedef SmartPointer< Self > Pointer;
typedef SmartPointer< const Self > ConstPointer;
/** Inherited typedef from the superclass. */
typedef typename Superclass::ValueType ValueType;
typedef typename Superclass::IndexType IndexType;
typedef typename Superclass::TimeStepType TimeStepType;
typedef typename Superclass::InputImageType InputImageType;
/** Local image typedefs */
typedef TOutputImage OutputImageType;
typedef TFeatureImage FeatureImageType;
/** The generic level set function type */
typedef SegmentationLevelSetFunction< OutputImageType, FeatureImageType >
SegmentationFunctionType;
/** The type used for the advection field */
typedef typename SegmentationFunctionType::VectorImageType VectorImageType;
/** Run-time type information (and related methods). */
itkTypeMacro(NarrowBandLevelSetImageFilter, NarrowBandImageFilterBase);
/** Set/Get the feature image to be used for speed function of the level set
* equation. Equivalent to calling Set/GetInput(1, ..) */
virtual void SetFeatureImage(const FeatureImageType *f)
{
this->ProcessObject::SetNthInput( 1, const_cast< FeatureImageType * >( f ) );
m_SegmentationFunction->SetFeatureImage(f);
}
virtual FeatureImageType * GetFeatureImage()
{
return ( static_cast< FeatureImageType * >( this->ProcessObject::GetInput(1) ) );
}
/** Set/Get the initial level set model. Equivalent to calling SetInput(..)
*/
virtual void SetInitialImage(InputImageType *f)
{
this->SetInput(f);
}
virtual const typename SegmentationFunctionType::ImageType * GetSpeedImage() const
{ return m_SegmentationFunction->GetSpeedImage(); }
virtual const typename SegmentationFunctionType::VectorImageType * GetAdvectionImage() const
{ return m_SegmentationFunction->GetAdvectionImage(); }
/** THIS METHOD IS DEPRECATED AND SHOULD NOT BE USED. This method reverses
* the speed function direction, effectively changing inside feature values to
* outside feature values and vice versa. */
void SetUseNegativeFeaturesOn()
{
itkWarningMacro(
<< "SetUseNegativeFeaturesOn has been deprecated. Please use ReverseExpansionDirectionOn() instead");
this->ReverseExpansionDirectionOn();
}
void SetUseNegativeFeaturesOff()
{
itkWarningMacro(
<< "SetUseNegativeFeaturesOff has been deprecated. Please use ReverseExpansionDirectionOff() instead");
this->ReverseExpansionDirectionOff();
}
/** Set/Get the value of the UseNegativeFeatures flag. This method is
* deprecated. Use Set/Get ReverseExpansionDirection instead. */
void SetUseNegativeFeatures(bool u)
{
itkWarningMacro(<< "SetUseNegativeFeatures has been deprecated. Please use SetReverseExpansionDirection instead");
if ( u == true )
{
this->SetReverseExpansionDirection(false);
}
else
{
this->SetReverseExpansionDirection(true);
}
}
bool GetUseNegativeFeatures() const
{
itkWarningMacro(<< "GetUseNegativeFeatures has been deprecated. Please use GetReverseExpansionDirection() instead");
if ( this->GetReverseExpansionDirection() == false )
{
return true;
}
else
{
return false;
}
}
/** Turn On/Off the flag which determines whether Positive or Negative speed
* terms will cause surface expansion. If set to TRUE then negative speed
* terms will cause the surface to expand and positive speed terms will cause
* the surface to contract. If set to FALSE (default) then positive speed terms will
* cause the surface to expand and negative speed terms will cause the
* surface to contract. This method can be safely used to reverse the
* expansion/contraction as appropriate to a particular application or data
* set. */
itkSetMacro(ReverseExpansionDirection, bool);
itkGetConstMacro(ReverseExpansionDirection, bool);
itkBooleanMacro(ReverseExpansionDirection);
/** Combined scaling of the propagation and advection speed
terms. You should use either this -or- Get/SetPropagationScaling and
Get/SetAdvectionScaling (if appropriate). See subclasses for details
on when and whether to set these parameters. */
void SetFeatureScaling(ValueType v)
{
if ( v != m_SegmentationFunction->GetPropagationWeight() )
{
this->SetPropagationScaling(v);
}
if ( v != m_SegmentationFunction->GetAdvectionWeight() )
{
this->SetAdvectionScaling(v);
}
}
/** Set/Get the scaling of the propagation speed. Setting the FeatureScaling
parameter overrides any previous values set for PropagationScaling. */
void SetPropagationScaling(ValueType v)
{
if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetPropagationWeight()) )
{
m_SegmentationFunction->SetPropagationWeight(v);
}
}
ValueType GetPropagationScaling() const
{
return m_SegmentationFunction->GetPropagationWeight();
}
/** Set/Get the scaling of the advection field. Setting the FeatureScaling
parameter will override any existing value for AdvectionScaling. */
void SetAdvectionScaling(ValueType v)
{
if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetAdvectionWeight()) )
{
m_SegmentationFunction->SetAdvectionWeight(v);
}
}
ValueType GetAdvectionScaling() const
{
return m_SegmentationFunction->GetAdvectionWeight();
}
/** Set/Get the scaling of the curvature. Use this parameter to increase the
* influence of curvature on the movement of the surface. Higher
* values relative to Advection and Propagation values will give
* smoother surfaces. */
void SetCurvatureScaling(ValueType v)
{
if ( Math::NotExactlyEquals(v, m_SegmentationFunction->GetCurvatureWeight()) )
{
m_SegmentationFunction->SetCurvatureWeight(v);
}
}
ValueType GetCurvatureScaling() const
{
return m_SegmentationFunction->GetCurvatureWeight();
}
/** Set the segmentation function. In general, this should only be called by a subclass
* of this object. It is made public to allow itk::Command objects access. */
virtual void SetSegmentationFunction(SegmentationFunctionType *s);
virtual SegmentationFunctionType * GetSegmentationFunction()
{ return m_SegmentationFunction; }
/** Set/Get the maximum number of iterations allowed for the solver. This
* prevents infinite loops if a solution "bounces". */
void SetMaximumIterations(unsigned int i)
{
itkWarningMacro("SetMaximumIterations is deprecated. Please use SetNumberOfIterations instead.");
this->SetNumberOfIterations(i);
}
unsigned int GetMaximumIterations()
{
itkWarningMacro("GetMaximumIterations is deprecated. Please use GetNumberOfIterations instead.");
return this->GetNumberOfIterations();
}
virtual void SetMaximumRMSError(const double) ITK_OVERRIDE
{
itkWarningMacro(
"The current implmentation of this solver does not compute maximum RMS change. The maximum RMS error value will not be set or used.");
}
#ifdef ITK_USE_CONCEPT_CHECKING
// Begin concept checking
itkConceptMacro( OutputHasNumericTraitsCheck,
( Concept::HasNumericTraits< typename TOutputImage::PixelType > ) );
// End concept checking
#endif
protected:
virtual ~NarrowBandLevelSetImageFilter() ITK_OVERRIDE {}
NarrowBandLevelSetImageFilter();
virtual void PrintSelf(std::ostream & os, Indent indent) const ITK_OVERRIDE;
/** Overrides parent implementation */
virtual void InitializeIteration() ITK_OVERRIDE
{
Superclass::InitializeIteration();
// Estimate the progress of the filter
this->UpdateProgress( (float)( (float)this->GetElapsedIterations()
/ (float)this->GetNumberOfIterations() ) );
}
/** Tells the solver how to reinitialize the narrowband when the reinitialization
* criterion meets */
virtual void CreateNarrowBand() ITK_OVERRIDE;
/** Overridden from ProcessObject to set certain values before starting the
* finite difference solver and then create an appropriate output */
void GenerateData() ITK_OVERRIDE;
/** Flag which sets the inward/outward direction of propagation speed. See
SetReverseExpansionDirection for more information. */
bool m_ReverseExpansionDirection;
/** Reinitialization filters **/
/** Internal filter types used for reinitialization */
typedef IsoContourDistanceImageFilter< OutputImageType, OutputImageType >
IsoFilterType;
typedef FastChamferDistanceImageFilter< OutputImageType, OutputImageType >
ChamferFilterType;
typename IsoFilterType::Pointer m_IsoFilter;
typename ChamferFilterType::Pointer m_ChamferFilter;
private:
ITK_DISALLOW_COPY_AND_ASSIGN(NarrowBandLevelSetImageFilter);
SegmentationFunctionType *m_SegmentationFunction;
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkNarrowBandLevelSetImageFilter.hxx"
#endif
#endif
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