ITK: itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage

Inheritance diagram for itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >:

Detailed Description

template<class TInputImage, class TOutputImage>
class itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >

There are four basic concepts in fuzzy connectedness: fuzzy affinity [1,2], fuzzy connectedness [1], scale [2], and relative fuzzy connectedness [3]. These references give a complete theoretical basis and description of the underlying algorithms. For algorithm implementation and efficiency, see [4].

Fuzzy affinity is a local fuzzy relation which is defined on the whole image domain. It assigns to every pair of nearby voxels a strength of local hanging togetherness. Two components of fuzzy affinity named homogeneity-feature-based affinity and object-feature-based affinity are devised in a fully vectorial manner. The strength of affinity between any two nearby voxels v1 and v2 is large when v1 and v2 are spatially close, the intensity vectors of voxels in the "vicinity" of v1 and v2 have a high degree of homogeneity, and the intensity vectors are close to an intensity vector expected for the object of interest. (If v1 and v2 are far apart, their affinity is considered to be 0) The extent of "vicinity" is determined by the "scale" value assigned to v1 and v2.

"Scale" is a number assigned to every voxel in the image. It represents the radius of the largest ball centered at the voxel within which the vectorial values of all voxels are homogeneous. In determining affinity between two voxels, all voxels within the ball associated with both voxels are considered. Scale-based fuzzy affinity and fuzzy connectedness can make our algorithms more robust and less sensitive to noise.

A global fuzzy relation called fuzzy connectedness is defined on the whole image domain which assigns to every pair of voxels a strength of global hanging togetherness. The strength of hanging togetherness (connectedness) between two voxels is the largest of the strengths of all paths between them. The strength of any path is simply the smallest affinity of successive pair of voxels along the path.

The other important concept is relative fuzzy connectedness. An object gets defined in an image because of the presence of other co-objects. All co-objects of importance that are present in an image are let to compete among themselves in having voxels as their members. In this competition, every pair of voxels in the image will have a strength of connectedness in each object. The object in which this strength is highest will claim membership of the voxels. Suppose that there are n objects (note that image background is also an object) in the image and that we specify a seed voxel si in each object. Then any voxel v in the image has a strength of connectedness with respect to each si. Voxel v is considered to belong to that object with respect to whose seed v has the highest strength of connectedness [3]. The method requires some modification when a set of seed voxels is specified for each object. The basic algorithmic tool required in all cases is dynamic programming.

The fuzzy connectedness methods have been utilized on 1000s of images in several applications [6-10].

Our program takes a vectorial image as input and produces one binary output. The procedure includes six main steps. 1. Use function Compute_LookupTable () to setup three look-up tables m_ScaleMap, m_HomogeneityMap and m_ObjectMap in order to facilitate the computation of scale, homogeneity-based affinity and object-feature-based * affinity. 2. Use function Compute_Scale() to compute scale value at every voxel in and keep them in m_ScaleArray. In our program we set the maximum scale value as 8, this value could be changed in terms of the input image. 3. Use function Compute_Filter() to compute scale-based filtered vectorial value at every voxel and keep the value in m_FilterImage, this step is to speed up the computation of next step. 4. Use function Compute_Affinity() to compute fuzzy affinity value of each pair of neighboring voxels and keep them in m_Xaffinity, m_Yaffinity, and m_Zaffinity in terms of the coordinate direction. At first, we compute homogeneity-based affinity, them compute object-feature-based affinity, finally we combine them together. 5. Use function FastTracking() to compute global fuzzy connectedness between every voxel and seed points of foreground (selected object) and compute global fuzzy connectedness between every voxel and seed points of background ( other objects). And keep their values in m_ObjectFuzzyScene and m_BackgroundFuzzyScene respectively. 6. In function GenerateDate(), we implement iterative relative fuzzy connectedness strategy. We let foreground and background to compete between them for having voxels as their members in an iterative fashion [5].

1. Use function SetObjects to set the number of objects of importance in the image. 2. Use function SetSelectedObject to specify the particular object to be segmented. 3. Use function SetObjectsSeed to specify seed points for objects. 4. Use function SetObjectsMean to specify the mean value of the intensity vector for objects. 5. Use function SetObjectsMatrix to specify the covariance matrix of the intensity vector for objects.

1. J. K. Udupa and S. Samarasekera, Fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation, Graphical Models Image Processing 58, 1996, 246-261. 2. P. K. Saha, J. K. Udupa, and D. Odhner, Scale-based fuzzy connected image segmentation: theory, algorithms, and validation, Computer Vision and Image Understanding 77, 2000, 145-174. 3. P. K.Saha and J. K. Udupa, Relative Fuzzy connectedness among multiple objects: Theory, algorithms, and applications in image segmentation, Computer Vision and Image Understanding 82, 2001, 42-56. 4. L. G. Nyul and J. K. Udupa, Fuzzy-connected 3D image segmentation at interactive speeds, Proc. SPIE: Medical Imaging 3979, 2000, 212-223. 5. P. K.Saha and J. K. Udupa, Iterative relative fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation, in Proc. Of IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2000, 28-35. 6. J. K. Udupa, L. Wei, S. Samarasekera, Y. Miki, M. A. van Buchen, and R. I. Grossman, Multiple sclerosis lesion quantification using fuzzy connected principles, IEEE Trans. Med. Imag. 16(5), 1997, 598-609. 7. B. L. Rice and J. K. Udupa, Fuzzy connected clutter-free volume rendering for MR angiography, Int. J. Imaging System. Tech. 11, 2000, 62-70. 8. T. Lei and J. K. Udupa, Artery-Vein Separation via MRA-An Image Processing Approch, IEEE Trans. Med. Imag. 20(8), 2001, 689-703. 9. P. K. Saha, J. K. Udupa, E. F. conant, D. P. Chakraborty, and D. Sullivan, Breast Tissue density Quantification via Digitized Mammograms, IEEE Trans. Med. Imag. 20(8), 2001, 792-803. 10. J. Liu, J. K. Udupa, D. Hackney, and G. Moonis, Brain tumor segmentation in MRI by using the fuzzy connectedness method, Proc. SPIE: Medical Imaging 4322, 2001, 1455-1465.

Member Typedef Documentation

template<class TInputImage, class TOutputImage>

typedef Image<AffinityVector, itkGetStaticConstMacro(ImageDimension)> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::AffinityImageType

Definition at line 210 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef Vector<unsigned short,itkGetStaticConstMacro(ImageDimension)> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::AffinityVector

Vector of unsigned sStrong affinity type

Definition at line 196 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef SmartPointer<const Self> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::ConstPointer

Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.

Definition at line 169 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TOutputImage>

typedef DataObject::Pointer itk::ImageSource< TOutputImage >::DataObjectPointer [inherited]

Smart Pointer type to a DataObject.

Reimplemented from itk::ProcessObject.

Reimplemented in itk::LabelStatisticsImageFilter< TInputImage, TLabelImage >, itk::MinimumMaximumImageFilter< TInputImage >, itk::StatisticsImageFilter< TInputImage >, and itk::StreamingImageFilter< TInputImage, TOutputImage >.

Definition at line 62 of file itkImageSource.h.

typedef std::vector<DataObjectPointer> itk::ProcessObject::DataObjectPointerArray [inherited]

STL Array of SmartPointers to DataObjects

Definition at line 103 of file itkProcessObject.h.

typedef DataObjectPointerArray::size_type itk::ProcessObject::DataObjectPointerArraySizeType [inherited]

Size type of an std::vector

Definition at line 112 of file itkProcessObject.h.

template<class TInputImage, class TOutputImage>

typedef std::vector<DoubleMatrixType> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::DoubleMatrixArrayType

Array of double matrics

Definition at line 193 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef Matrix<double, itkGetStaticConstMacro(VectorDimension), itkGetStaticConstMacro(VectorDimension)> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::DoubleMatrixType

Double matrix type

Definition at line 190 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef std::vector<DoubleVectorType> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::DoubleVectorArrayType

Array of double vectors

Definition at line 202 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef Vector<double, itkGetStaticConstMacro(VectorDimension)> itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::DoubleVectorType

Vector of double type

Definition at line 199 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef TInputImage::IndexType itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >::IndexType

Definition at line 213 of file itkVectorFuzzyConnectednessImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef InputImageType::ConstPointer itk::ImageToImageFilter< TInputImage, TOutputImage >::InputImageConstPointer [inherited]

Definition at line 84 of file itkImageToImageFilter.h.

template<class TInputImage, class TOutputImage>

typedef InputImageType::PixelType itk::ImageToImageFilter< TInputImage, TOutputImage >::InputImagePixelType [inherited]

Definition at line 86 of file itkImageToImageFilter.h.


Public Types
typedef Vector< unsigned short, itkGetStaticConstMacro(ImageDimension)>	AffinityVector
typedef SmartPointer< const Self >	ConstPointer
typedef DataObject::Pointer	DataObjectPointer
typedef std::vector< DataObjectPointer >	DataObjectPointerArray
typedef DataObjectPointerArray::size_type	DataObjectPointerArraySizeType
typedef std::vector< DoubleMatrixType >	DoubleMatrixArrayType
typedef Matrix< double, itkGetStaticConstMacro(VectorDimension), itkGetStaticConstMacro(VectorDimension)>	DoubleMatrixType
typedef std::vector< DoubleVectorType >	DoubleVectorArrayType
typedef Vector< double, itkGetStaticConstMacro(VectorDimension)>	DoubleVectorType
typedef TInputImage::IndexType	IndexType
typedef InputImageType::ConstPointer	InputImageConstPointer
typedef InputImageType::PixelType	InputImagePixelType
typedef InputImageType::Pointer	InputImagePointer
typedef InputImageType::RegionType	InputImageRegionType
typedef TInputImage::PixelType	InputPixelType
typedef InputPixelType::VectorType	InputVectorType
typedef std::vector< ListSeedType >	ListSeedArrayType
typedef std::list< IndexType >	ListSeedType
typedef std::vector< TDVector >	OffsetType
typedef Superclass::OutputImagePixelType	OutputImagePixelType
typedef OutputImageType::Pointer	OutputImagePointer
typedef Superclass::OutputImageRegionType	OutputImageRegionType
typedef TOutputImage::PixelType	OutputPixelType
typedef TOutputImage::RegionType	OutRegionType
typedef SmartPointer< Self >	Pointer
typedef VectorFuzzyConnectednessImageFilter	Self
typedef TInputImage::SizeType	SizeType
typedef ImageToImageFilter< TInputImage, TOutputImage >	Superclass
typedef Vector< int, 2 >	TDVector

typedef Image< AffinityVector, itkGetStaticConstMacro(ImageDimension)>	AffinityImageType
typedef TInputImage	InputImageType
typedef TOutputImage	OutputImageType
typedef Image< unsigned short, itkGetStaticConstMacro(ImageDimension)>	UShortImageType
Public Member Functions
virtual void	AbortGenerateDataOff ()
virtual void	AbortGenerateDataOn ()
virtual LightObject::Pointer	CreateAnother () const
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
virtual void	EnlargeOutputRequestedRegion (DataObject *)
virtual const bool &	GetAbortGenerateData ()
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
DataObjectPointerArray &	GetInputs ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
MultiThreader *	GetMultiThreader ()
virtual const char *	GetNameOfClass () const
DataObjectPointerArraySizeType	GetNumberOfInputs () const
virtual DataObjectPointerArraySizeType	GetNumberOfValidRequiredInputs () const
virtual const float &	GetProgress ()
virtual int	GetReferenceCount () const
virtual void	GraftNthOutput (unsigned int idx, DataObject *output)
virtual void	GraftOutput (DataObject *output)
bool	HasObserver (const EventObject &event) const
void	Initialization ()
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual DataObjectPointer	MakeOutput (unsigned int idx)
virtual void	Modified () const
virtual void	PrepareOutputs ()
void	Print (std::ostream &os, Indent indent=0) const
virtual void	PropagateRequestedRegion (DataObject *output)
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual void	ResetPipeline ()
virtual void	SetAbortGenerateData (bool _arg)
void	SetDebug (bool debugFlag) const
void	SetHomogeneityMatrix (const DoubleMatrixType homo_max)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetObjectsMatrix (const DoubleMatrixType object_max, const int object_num)
void	SetObjectsMean (const DoubleVectorType, const int object_num)
void	SetObjectsSeed (const IndexType &seed, const int object_num)
virtual void	SetProgress (float _arg)
virtual void	SetReferenceCount (int)
void	SetSuppressBckgFlag (const int flag)
void	SetThreshold (const float threshold)
virtual void	UnRegister () const
virtual void	Update ()
virtual void	UpdateLargestPossibleRegion ()
virtual void	UpdateOutputData (DataObject *output)
virtual void	UpdateOutputInformation ()
void	UpdateProgress (float amount)

unsigned long	AddObserver (const EventObject &event, Command *) const
unsigned long	AddObserver (const EventObject &event, Command *)

const InputImageType *	GetInput (unsigned int idx)
const InputImageType *	GetInput (void)
virtual void	SetInput (unsigned int, const TInputImage *image)
virtual void	SetInput (const InputImageType *image)

virtual int	GetNumberOfObjects ()
virtual void	SetNumberOfObjects (int _arg)

DataObjectPointerArraySizeType	GetNumberOfOutputs () const
DataObjectPointerArray &	GetOutputs ()

virtual const int &	GetNumberOfThreads ()
virtual void	SetNumberOfThreads (int _arg)

OutputImageType *	GetOutput (unsigned int idx)
OutputImageType *	GetOutput (void)

virtual const bool &	GetReleaseDataBeforeUpdateFlag ()
virtual void	ReleaseDataBeforeUpdateFlagOff ()
virtual void	ReleaseDataBeforeUpdateFlagOn ()
virtual void	SetReleaseDataBeforeUpdateFlag (bool _arg)

virtual bool	GetReleaseDataFlag () const
void	ReleaseDataFlagOff ()
void	ReleaseDataFlagOn ()
virtual void	SetReleaseDataFlag (bool flag)

	itkStaticConstMacro (OutputImageDimension, unsigned int, TOutputImage::ImageDimension)
	itkStaticConstMacro (InputImageDimension, unsigned int, TInputImage::ImageDimension)

	itkStaticConstMacro (ImageDimension, unsigned int, TInputImage::ImageDimension)
	itkStaticConstMacro (VectorDimension, unsigned int, InputPixelType::Dimension)

virtual void	PopBackInput ()
virtual void	PopFrontInput ()
virtual void	PushBackInput (const InputImageType *image)
virtual void	PushFrontInput (const InputImageType *image)
Static Public Member Functions
static void	BreakOnError ()
static Pointer	New ()

static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static void	SetGlobalWarningDisplay (bool flag)
Protected Types
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension)>	InputToOutputRegionCopierType
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension)>	OutputToInputRegionCopierType
Protected Member Functions
virtual void	AfterThreadedGenerateData ()
virtual void	AllocateOutputs ()
virtual void	BeforeThreadedGenerateData ()
virtual void	CacheInputReleaseDataFlags ()
virtual void	CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
virtual void	CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
void	GenerateData ()
virtual void	GenerateInputRequestedRegion ()
virtual void	GenerateOutputInformation ()
virtual void	GenerateOutputRequestedRegion (DataObject *output)
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PropagateResetPipeline ()
virtual void	ReleaseInputs ()
virtual void	RestoreInputReleaseDataFlags ()
void	SetNumberOfInputs (unsigned int num)
void	SetNumberOfOutputs (unsigned int num)
virtual int	SplitRequestedRegion (int i, int num, OutputImageRegionType &splitRegion)
virtual void	ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, int threadId) ITK_NO_RETURN
	VectorFuzzyConnectednessImageFilter ()
	~VectorFuzzyConnectednessImageFilter ()

virtual void	AddInput (DataObject *input)
virtual const unsigned int &	GetNumberOfRequiredInputs ()
virtual void	RemoveInput (DataObject *input)
virtual void	SetNthInput (unsigned int num, DataObject *input)
virtual void	SetNumberOfRequiredInputs (unsigned int _arg)

virtual void	AddOutput (DataObject *output)
virtual const unsigned int &	GetNumberOfRequiredOutputs ()
virtual void	RemoveOutput (DataObject *output)
virtual void	SetNthOutput (unsigned int num, DataObject *output)
virtual void	SetNumberOfRequiredOutputs (unsigned int _arg)

const DataObject *	GetInput (unsigned int idx) const

const DataObject *	GetOutput (unsigned int idx) const

virtual void	PrintHeader (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const

void	PushBackInput (const DataObject *input)
void	PushFrontInput (const DataObject *input)
Static Protected Member Functions
static ITK_THREAD_RETURN_TYPE	ThreaderCallback (void *arg)
Protected Attributes
TimeStamp	m_OutputInformationMTime
volatile int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
bool	m_Updating

itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage > Class Template Reference [Fuzzy Connectedness-based Segmentation Filters]

Detailed Description

template<class TInputImage, class TOutputImage> class itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Member Typedef Documentation

itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage > Class Template Reference
[Fuzzy Connectedness-based Segmentation Filters]

template<class TInputImage, class TOutputImage>
class itk::VectorFuzzyConnectednessImageFilter< TInputImage, TOutputImage >