#include <itkMRIBiasFieldCorrectionFilter.h>

Inheritance diagram for itk::MRIBiasFieldCorrectionFilter< TInputImage, TOutputImage, TMaskImage >:

Collaboration diagram for itk::MRIBiasFieldCorrectionFilter< TInputImage, TOutputImage, TMaskImage >:

Public Types
typedef MultivariateLegendrePolynomial	BiasFieldType
typedef SmartPointer< const Self >	ConstPointer
typedef EnergyFunctionType::Pointer	EnergyFunctionPointer
typedef MRIBiasEnergyFunction < InternalImageType, ImageMaskType, BiasFieldType >	EnergyFunctionType
typedef ImageMaskType::Pointer	ImageMaskPointer
typedef ImageMaskType::RegionType	ImageMaskRegionType
typedef TMaskImage	ImageMaskType
typedef TInputImage::IndexType	InputImageIndexType
typedef TInputImage::PixelType	InputImagePixelType
typedef TInputImage::Pointer	InputImagePointer
typedef TInputImage::RegionType	InputImageRegionType
typedef TInputImage::SizeType	InputImageSizeType
typedef TInputImage	InputImageType
typedef MRASlabIdentifier < InputImageType >	MRASlabIdentifierType
typedef Statistics::NormalVariateGenerator	NormalVariateGeneratorType
typedef OnePlusOneEvolutionaryOptimizer	OptimizerType
typedef TOutputImage::IndexType	OutputImageIndexType
typedef TOutputImage::PixelType	OutputImagePixelType
typedef TOutputImage::Pointer	OutputImagePointer
typedef TOutputImage::RegionType	OutputImageRegionType
typedef TOutputImage::SizeType	OutputImageSizeType
typedef TOutputImage	OutputImageType
typedef SmartPointer< Self >	Pointer
typedef Array2D< unsigned int >	ScheduleType
typedef MRIBiasFieldCorrectionFilter	Self
typedef SlabRegionVectorType::iterator	SlabRegionVectorIteratorType
typedef MRASlabIdentifierType::SlabRegionVectorType	SlabRegionVectorType
typedef ImageToImageFilter < TInputImage, TOutputImage >	Superclass

typedef Image< float, itkGetStaticConstMacro(ImageDimension) >	InternalImageType
typedef InternalImageType::PixelType	InternalImagePixelType
typedef InternalImageType::Pointer	InternalImagePointer
typedef InternalImageType::RegionType	InternalImageRegionType
Public Member Functions
void	CorrectImage (BiasFieldType &bias, InputImageRegionType region)
void	CorrectInterSliceIntensityInhomogeneity (InputImageRegionType region)
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
BiasFieldType	EstimateBiasField (InputImageRegionType region, unsigned int degree, int maximumIteration)
BiasFieldType::CoefficientArrayType	GetEstimatedBiasFieldCoefficients ()
virtual ImageMaskType *	GetInputMask ()
virtual const char *	GetNameOfClass () const
virtual unsigned int	GetNumberOfLevels () const
virtual double	GetOptimizerShrinkFactor () const
virtual ImageMaskType *	GetOutputMask ()
virtual const ScheduleType &	GetSchedule ()
virtual const InputImagePixelType &	GetSlabBackgroundMinimumThreshold ()
virtual const unsigned int &	GetSlabNumberOfSamples ()
virtual const double &	GetSlabTolerance ()
const unsigned int *	GetStartingShrinkFactors () const
void	Initialize () throw ( ExceptionObject )
void	IsBiasFieldMultiplicative (bool flag)
bool	IsBiasFieldMultiplicative ()
void	SetInitialBiasFieldCoefficients (const BiasFieldType::CoefficientArrayType &coefficients)
void	SetInputMask (ImageMaskType *inputMask)
void	SetNumberOfLevels (unsigned int num)
virtual void	SetOptimizerShrinkFactor (double _arg)
void	SetOutputMask (ImageMaskType *outputMask)
void	SetSchedule (const ScheduleType &schedule)
virtual void	SetSlabBackgroundMinimumThreshold (InputImagePixelType _arg)
virtual void	SetSlabNumberOfSamples (unsigned int _arg)
virtual void	SetSlabTolerance (double _arg)
virtual void	SetSlicingDirection (int _arg)
void	SetStartingShrinkFactors (unsigned int factor)
void	SetStartingShrinkFactors (unsigned int *factors)
void	SetTissueClassStatistics (const Array< double > &means, const Array< double > &sigmas) throw ( ExceptionObject )

virtual void	SetUsingInterSliceIntensityCorrection (bool _arg)
virtual const bool &	GetUsingInterSliceIntensityCorrection ()

virtual void	SetUsingSlabIdentification (bool _arg)
virtual const bool &	GetUsingSlabIdentification ()

virtual void	SetUsingBiasFieldCorrection (bool _arg)
virtual const bool &	GetUsingBiasFieldCorrection ()

virtual void	SetGeneratingOutput (bool _arg)
virtual const bool &	GetGeneratingOutput ()

virtual void	SetBiasFieldDegree (int _arg)
virtual int	GetBiasFieldDegree () const

virtual void	SetVolumeCorrectionMaximumIteration (int _arg)
virtual int	GetVolumeCorrectionMaximumIteration () const
virtual void	SetInterSliceCorrectionMaximumIteration (int _arg)
virtual int	GetInterSliceCorrectionMaximumIteration () const

void	SetOptimizerInitialRadius (double initRadius)
double	GetOptimizerInitialRadius ()

virtual void	SetOptimizerGrowthFactor (double _arg)
virtual double	GetOptimizerGrowthFactor () const
Static Public Member Functions
static bool	IsScheduleDownwardDivisible (const ScheduleType &schedule)
static Pointer	New ()
Static Public Attributes
static const unsigned int	ImageDimension = TOutputImage::ImageDimension
Protected Member Functions
void	AdjustSlabRegions (SlabRegionVectorType &slabs, OutputImageRegionType requestedRegion)
bool	CheckMaskImage (ImageMaskType *mask)
template<class TSource , class TTarget >
void	CopyAndConvertImage (const TSource source, TTarget target, typename TTarget::RegionType requestedRegion)
void	ExpImage (InternalImageType source, InternalImageType target)
void	GenerateData ()
void	GetBiasFieldSize (InputImageRegionType region, BiasFieldType::DomainSizeType &domainSize)
void	Log1PImage (InternalImageType source, InternalImageType target)
	MRIBiasFieldCorrectionFilter ()
void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~MRIBiasFieldCorrectionFilter ()
Private Member Functions
	MRIBiasFieldCorrectionFilter (const Self &)
void	operator= (const Self &)
Private Attributes
BiasFieldType::CoefficientArrayType	m_BiasFieldCoefficients
int	m_BiasFieldDegree
bool	m_BiasMultiplicative
EnergyFunctionPointer	m_EnergyFunction
BiasFieldType::CoefficientArrayType	m_EstimatedBiasFieldCoefficients
bool	m_GeneratingOutput
ImageMaskPointer	m_InputMask
InternalImagePointer	m_InternalInput
int	m_InterSliceCorrectionMaximumIteration
NormalVariateGeneratorType::Pointer	m_NormalVariateGenerator
unsigned int	m_NumberOfLevels
double	m_OptimizerGrowthFactor
double	m_OptimizerInitialRadius
double	m_OptimizerShrinkFactor
ImageMaskPointer	m_OutputMask
ScheduleType	m_Schedule
InputImagePixelType	m_SlabBackgroundMinimumThreshold
unsigned int	m_SlabNumberOfSamples
SlabRegionVectorType	m_Slabs
double	m_SlabTolerance
int	m_SlicingDirection
Array< double >	m_TissueClassMeans
Array< double >	m_TissueClassSigmas
bool	m_UsingBiasFieldCorrection
bool	m_UsingInterSliceIntensityCorrection
bool	m_UsingSlabIdentification
int	m_VolumeCorrectionMaximumIteration

Detailed Description

template<class TInputImage, class TOutputImage, class TMaskImage>
class itk::MRIBiasFieldCorrectionFilter< TInputImage, TOutputImage, TMaskImage >

corrects 3D MRI bias field

This class is templated over the type of the input image (TInputImage) and the type of the output image (TOutputImage).

In MRI images, intensity inhomogenieties which are caused by magnetic settings, patients' postion, and other factors are not unusual. The main purpose of this filter is to reduce such bias field. To estimate the bias field, we use Legendre polynomials. The 1+1 evolutionary optimizer searches for the best parameters of a Legendre polynomial (bias field estimate) which minimizes the total energy value of each image after bias field is eleminated. The default Legendre polynomial degree is 3.

The correction performes by default a multiplicative bias field correction by first log-transforming the input image. This log transform only works on images with grayscale values bigger than 0. The log-transform can be disabled and the filter computes an additive bias field.

There are three major processes in the whole bias correction scheme: slab identification, inter-slice intensity correction, and actual bias correction process. Users can turn on and off each process within the whole bias correction scheme using SetUsingSlabIdentification(bool, false by default), SetUsingInterSliceIntensityCorrection(bool, true by default), and SetUsingBiasFieldCorrection(bool, true by default) member function.

Only the last process (the actual bias field correction) is implemented in a multiresolution framework (without smoothing). Default is a standard level 2 multiresolution schedule (2 2 2 1 1 1)

The bias field correction method was initially developed and implemented by Martin Styner, Univ. of North Carolina at Chapel Hill, and his colleagues.

The multiresolution pyramid implementation is based on itkMultiTesolutionPyramidImageFilter (without Gaussian smoothing)

For more details. refer to the following articles. "Parametric estimate of intensity inhomogeneities applied to MRI" Martin Styner, Guido Gerig, Christian Brechbuehler, Gabor Szekely, IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000, (http://www.cs.unc.edu/~styner/docs/tmi00.pdf)

"Evaluation of 2D/3D bias correction with 1+1ES-optimization" Martin Styner, Prof. Dr. G. Gerig (IKT, BIWI, ETH Zuerich), TR-197 (http://www.cs.unc.edu/~styner/docs/StynerTR97.pdf)

Definition at line 224 of file itkMRIBiasFieldCorrectionFilter.h.