itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType > Class Template Reference
[Multithreaded Filters]

#include <itkDiffusionTensor3DReconstructionImageFilter.h>

Inheritance diagram for itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >:

[legend]Collaboration diagram for itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >:

[legend]List of all members.

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Detailed Description

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double>
class itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >

This class takes as input one or more reference image (acquired in the absence of diffusion sensitizing gradients) and 'n' diffusion weighted images and their gradient directions and computes an image of tensors. (with DiffusionTensor3D as the pixel type). Once that is done, you can apply filters on this tensor image to compute FA, ADC, RGB weighted maps etc.

Inputs and Usage

There are two ways to use this class. When you have one reference image and n gradient images, you would use the class as

       filter->SetReferenceImage( image0 );
       filter->AddGradientImage( direction1, image1 );
       filter->AddGradientImage( direction2, image2 );
   ...

When you have the 'n' gradient and one or more reference images in a single multi-component image (VectorImage), you can specify the images simply as

       filter->SetGradientImage( directionsContainer, vectorImage );

Note that this method is used to specify both the reference and gradient images. This is convenient when the DWI images are read in using the NRRD format. Like the Nrrd format, the reference images are those components of the vectorImage whose gradient direction is (0,0,0). If more than one reference image is present, they are averaged prior to applying the Stejskal-Tanner equations.

Outputs

The output image is an image of Tensors:

       Image< DiffusionTensor3D< TTensorPixelType >, 3 >

Parameters

• Threshold - Threshold on the reference image data. The output tensor will be a null tensor for pixels in the reference image that have a value less than this.
• BValue - See the documentation of SetBValue().
• At least 6 gradient images must be specified for the filter to be able to run.

Template parameters

The class is templated over the pixel type of the reference and gradient images (expected to be scalar data types) and the internal representation of the DiffusionTensor3D pixel (double, float etc).

References:

• [1] C.F.Westin, S.E.Maier, H.Mamata, A.Nabavi, F.A.Jolesz, R.Kikinis, "Processing and visualization for Diffusion tensor MRI", Medical image Analysis, 2002, pp 93-108.
• [2] A Dual Tensor Basis Solution to the Stejskal-Tanner Equations for DT-MRI

WARNING:

Although this filter has been written to support multiple threads, please set the number of threads to 1.

         filter->SetNumberOfThreads(1);

This is due to buggy code in netlib/dsvdc, that is called by vnl_svd. (used to compute the psudo-inverse to find the dual tensor basis).

Author:

Thanks to Xiaodong Tao, GE, for contributing parts of this class. Also thanks to Casey Goodlet, UNC for patches to support multiple baseline images and other improvements.

Note:

This work is part of the National Alliance for Medical image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Examples and Datasets

See Examples/Filtering/DiffusionTensor3DReconstructionImageFilter.cxx Sample DTI datasets may be obtained from verbatim ftp://public.kitware.com/pub/namic/DTI/Data/dwi.nhdr ftp://public.kitware.com/pub/namic/DTI/Data/dwi.img.gz ( gunzip this ) verbatim

See also:

DiffusionTensor3D SymmetricSecondRankTensor Objects Related to Tensor Images

Definition at line 122 of file itkDiffusionTensor3DReconstructionImageFilter.h.

Public Types
typedef vnl_matrix< double >	CoefficientMatrixType
typedef SmartPointer< const Self >	ConstPointer
typedef DataObject::Pointer	DataObjectPointer
typedef std::vector< DataObjectPointer >	DataObjectPointerArray
typedef VectorContainer< unsigned int, GradientDirectionType >	GradientDirectionContainerType
typedef vnl_vector_fixed< double, 3 >	GradientDirectionType
typedef VectorImage< GradientPixelType, 3 >	GradientImagesType
typedef Image< GradientPixelType, 3 >	GradientImageType
typedef TGradientImagePixelType	GradientPixelType
typedef InputImageType::ConstPointer	InputImageConstPointer
typedef InputImageType::PixelType	InputImagePixelType
typedef InputImageType::Pointer	InputImagePointer
typedef InputImageType::RegionType	InputImageRegionType
typedef Image< TReferenceImagePixelType, 3 >	InputImageType
typedef OutputImageType::PixelType	OutputImagePixelType
typedef OutputImageType::Pointer	OutputImagePointer
typedef Superclass::OutputImageRegionType	OutputImageRegionType
typedef TensorImageType	OutputImageType
typedef SmartPointer< Self >	Pointer
typedef Superclass::InputImageType	ReferenceImageType
typedef TReferenceImagePixelType	ReferencePixelType
typedef DiffusionTensor3DReconstructionImageFilter	Self
typedef ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >	Superclass
typedef vnl_matrix_fixed< double, 6, 6 >	TensorBasisMatrixType
typedef Image< TensorPixelType, 3 >	TensorImageType
typedef DiffusionTensor3D< TTensorPixelType >	TensorPixelType
Public Member Functions
virtual void	AbortGenerateDataOff ()
virtual void	AbortGenerateDataOn ()
void	AddGradientImage (const GradientDirectionType &, const GradientImageType *image)
virtual LightObject::Pointer	CreateAnother () const
virtual void	DebugOff () const
virtual void	DebugOn () const
virtual void	Delete ()
virtual void	EnlargeOutputRequestedRegion (DataObject *)
*The BValue	f (s/mm^2)\f $value used in normalizing the tensors to *physically meaningful units.See equation(24) of the first reference for *a description of how this is applied to the tensor estimation.*Equation(1) of the same reference describes the physical significance.*/virtual void SetBValue(TTensorPixelType _arg)
virtual const bool &	GetAbortGenerateData ()
virtual const TTensorPixelType &	GetBValue ()
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
Return the gradient direction idx is based *virtual GradientDirectionType	GetGradientDirection (unsigned int idx) const
const InputImageType *	GetInput (unsigned int idx)
const InputImageType *	GetInput (void)
DataObjectPointerArray &	GetInputs ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
virtual unsigned long	GetMTime () const
MultiThreader *	GetMultiThreader ()
virtual const char *	GetNameOfClass () const
std::vector< DataObjectPointer >::size_type	GetNumberOfInputs () const
std::vector< DataObjectPointer >::size_type	GetNumberOfOutputs () const
virtual const int &	GetNumberOfThreads ()
virtual std::vector< DataObjectPointer >::size_type	GetNumberOfValidRequiredInputs () const
OutputImageType *	GetOutput (unsigned int idx)
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *	GetOutput () and make sure the data is valid.In these *examples
Return an array with all the outputs of this process object *This is useful for tracing forward in the pipeline to contruct *graphs etc *DataObjectPointerArray &	GetOutputs ()
virtual const float &	GetProgress ()
virtual int	GetReferenceCount () const
virtual ReferenceImageType *	GetReferenceImage ()
virtual const bool &	GetReleaseDataBeforeUpdateFlag ()
virtual bool	GetReleaseDataFlag () const
virtual ReferencePixelType	GetThreshold ()
virtual void	GraftNthOutput (unsigned int idx, DataObject *output)
virtual void	GraftOutput (DataObject *output)
bool	HasObserver (const EventObject &event) const
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *a image is a pointer to some Image and the *particular ProcessObjects involved are filters The same *examples apply to non	image (e.g.Mesh) data as well.**\code *anotherFilter->SetInput(someFilter->GetOutput())
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
	itkStaticConstMacro (OutputImageDimension, unsigned int, Image< DiffusionTensor3D< TTensorPixelType >, 3 >::ImageDimension)
ImageDimension constants *	itkStaticConstMacro (InputImageDimension, unsigned int, Image< TReferenceImagePixelType, 3 >::ImageDimension)
virtual DataObjectPointer	MakeOutput (unsigned int idx)
virtual void	Modified () const
virtual void	PopBackInput ()
virtual void	PopFrontInput ()
virtual void	PrepareOutputs ()
void	Print (std::ostream &os, Indent indent=0) const
virtual void	PropagateRequestedRegion (DataObject *output)
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on then *run the filter on then run the filter on the application can accomplish this by popping *an input off the front of the input list and push a new image *onto the back of input list this only makes sense for *filters that single type of input **Other uses are also possible For a single input pushing *and popping inputs allow the application to temporarily replace *an input to a filter **virtual void	PushBackInput (const InputImageType *image)
virtual void	PushFrontInput (const InputImageType *image)
virtual void	Register () const
virtual void	ReleaseDataBeforeUpdateFlagOff ()
virtual void	ReleaseDataBeforeUpdateFlagOn ()
void	ReleaseDataFlagOff ()
void	ReleaseDataFlagOn ()
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
virtual void	ResetPipeline ()
virtual void	SetAbortGenerateData (bool _arg)
void	SetDebug (bool debugFlag) const
void	SetGradientImage (GradientDirectionContainerType *, const GradientImagesType *image)
virtual void	SetInput (unsigned int, const Image< TReferenceImagePixelType, 3 > *image)
Set Get the image input of this process object *virtual void	SetInput (const InputImageType *image)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
Get Set the number of threads to create when executing *virtual void	SetNumberOfThreads (int _arg)
virtual void	SetProgress (float _arg)
virtual void	SetReferenceCount (int)
void	SetReferenceImage (ReferenceImageType *referenceImage)
Turn on off the flags to control whether the bulk data belonging *to the outputs of this ProcessObject are released after being *used by a downstream ProcessObject Default value is off Another *options for controlling memory utilization is the *ReleaseDataBeforeUpdateFlag *virtual void	SetReleaseDataFlag (bool flag)
Threshold on the reference image data The output tensor will be a null *tensor for pixels in the reference image that have a value less than this *threshold *virtual void	SetThreshold (ReferencePixelType _arg)
virtual void	UnRegister () const
*endcode *In the above the two lines of code can be in *either order **Note that it may be more efficient to *use a pipeline than to call	Update () once for each filter in *turn.**For an image
*endcode *In the above the two lines of code can be in *either order **Note that	Update () is not called automatically except within a *pipeline as in the first example.When\b streaming(using a *StreamingImageFilter) is activated
*endcode **code *someFilter	Update ()
*image	Update ()
*anotherFilter	Update ()
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have	Update () methods
Get the output data of this process object The output of this *function is not valid until an appropriate	Update () method has *been called
virtual void	UpdateLargestPossibleRegion ()
virtual void	UpdateOutputData (DataObject *output)
virtual void	UpdateOutputInformation ()
void	UpdateProgress (float amount)
Static Public Member Functions
static void	BreakOnError ()
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
This is a global flag that controls whether any warning *or error messages are displayed *static void	SetGlobalWarningDisplay (bool flag)
Public Attributes
Allow people to add remove invoke observers(callbacks) to any ITK *object.This is an implementation of the subject/observer design *pattern.An observer is added by specifying an event to respond to *and an itk unsigned lon	AddObserver )(const EventObject &event, Command *) const
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on then *run the filter on then run the filter on the application can accomplish this by popping *an input off the front of the input list and push a new image *onto the back of input list	Again
This is a global flag that controls whether any	debug
*endcode *In the above	example
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on then *run the filter on then run the filter on the application can accomplish this by popping *an input off the front of the input list and push a new image *onto the back of input list this only makes sense for *filters that single type of input **Other uses are also possible For a single input	filter
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all	filters
*	image
*endcode **In this a someFilter and a anotherFilter are said *to constitute a b pipeline **code *	image
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on then *run the filter on then run the filter on *	images
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on then *run the filter on	images
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For if an application has *images and they need to run a filter on	images
Push Pop the input of this process object These methods allow a *filter to model its input vector as a queue or stack These *routines may not be appropriate for all especially *filters with different types of inputs These routines follow *the semantics of STL **The routines are useful for applications that need to process *rolling sets of images For	instance
Get the output data of this process object The output of this *function is not valid until an appropriate either explicitly or implicitly Both the filter *itself and the data object have and both *methods update the data Here are three ways to use *a image is a pointer to some Image	object
*endcode *In the above the two lines of code can be in *either order **Note that it may be more efficient to *use a pipeline than to call the data generated is for the requested *	Region
*endcode **In this	situation
Protected Types
enum	GradientImageTypeEnumeration {   GradientIsInASingleImage = 1,   GradientIsInManyImages,   Else }
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension)	InputToOutputRegionCopierType )
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension)	OutputToInputRegionCopierType )
Protected Member Functions
virtual void	AddInput (DataObject *input)
virtual void	AddOutput (DataObject *output)
virtual void	AfterThreadedGenerateData ()
virtual void	AllocateOutputs ()
void	BeforeThreadedGenerateData ()
virtual void	CacheInputReleaseDataFlags ()
virtual void	CallCopyInputRegionToOutputRegion (OutputImageRegionType &destRegion, const InputImageRegionType &srcRegion)
virtual void	CallCopyOutputRegionToInputRegion (InputImageRegionType &destRegion, const OutputImageRegionType &srcRegion)
void	ComputeTensorBasis ()
	DiffusionTensor3DReconstructionImageFilter ()
virtual void	GenerateData ()
virtual void	GenerateInputRequestedRegion ()
virtual void	GenerateOutputInformation ()
virtual void	GenerateOutputRequestedRegion (DataObject *output)
const DataObject *	GetInput (unsigned int idx) const
virtual const unsigned int &	GetNumberOfRequiredInputs ()
virtual const unsigned int &	GetNumberOfRequiredOutputs ()
const DataObject *	GetOutput (unsigned int idx) const
	ImageSource ()
	ImageToImageFilter ()
bool	PrintObservers (std::ostream &os, Indent indent) const
void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual void	PropagateResetPipeline ()
**these methods end of hiding the versions from the superclass *ProcessObject whose arguments are DataObjects we re expose *the versions from ProcessObject to avoid warnings about hiding *methods from the superclass *void	PushBackInput (const DataObject *input)
*	PushBackInput ()
*	PushFronInput () in the public section force the *input to be the type expected by an ImageToImageFilter.However
void	PushFrontInput (const DataObject *input)
virtual void	ReleaseInputs ()
virtual void	RemoveInput (DataObject *input)
virtual void	RemoveOutput (DataObject *output)
virtual void	RestoreInputReleaseDataFlags ()
Protected methods for setting inputs *Subclasses make use of them for setting input *virtual void	SetNthInput (unsigned int num, DataObject *input)
Protected methods for setting outputs *Subclasses make use of them for getting output *virtual void	SetNthOutput (unsigned int num, DataObject *output)
void	SetNumberOfInputs (unsigned int num)
void	SetNumberOfOutputs (unsigned int num)
virtual void	SetNumberOfRequiredInputs (unsigned int _arg)
virtual void	SetNumberOfRequiredOutputs (unsigned int _arg)
virtual int	SplitRequestedRegion (int i, int num, OutputImageRegionType &splitRegion)
void	ThreadedGenerateData (const OutputImageRegionType &outputRegionForThread, int)
	~DiffusionTensor3DReconstructionImageFilter ()
Static Protected Member Functions
static ITK_THREAD_RETURN_TYPE	ThreaderCallback (void *arg)
Protected Attributes
**these methods end of hiding the versions from the superclass *ProcessObject whose arguments are DataObjects	Here
TimeStamp	m_OutputInformationMTime
int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
bool	m_Updating
Methods invoked by virtual Print() to print information about the object *including superclasses.Typically not called by the user(use Print()*instead) but used in the hierarchical print process to combine the *output of several classes.*/virtual void PrintSelf(std voi	PrintHeader )(std::ostream &os, Indent indent) const

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Member Typedef Documentation

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef vnl_matrix< double > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::CoefficientMatrixType

Definition at line 172 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef SmartPointer<const Self> itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::ConstPointer

Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 131 of file itkDiffusionTensor3DReconstructionImageFilter.h.

typedef DataObject::Pointer itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::DataObjectPointer [inherited]

Smart Pointer type to a DataObject. Reimplemented from itk::ProcessObject. 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.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef VectorContainer< unsigned int, GradientDirectionType > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GradientDirectionContainerType

Container to hold gradient directions of the 'n' DW measurements Definition at line 179 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef vnl_vector_fixed< double, 3 > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GradientDirectionType

Holds each magnetic field gradient used to acquire one DWImage Definition at line 175 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef VectorImage< GradientPixelType, 3 > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GradientImagesType

An alternative typedef defining one (of the many) gradient images. It will be assumed that the vectorImage has the same dimension as the Reference image and a vector length parameter of n (number of gradient directions) Definition at line 167 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef Image< GradientPixelType, 3 > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GradientImageType

Typedef defining one (of the many) gradient images. Definition at line 161 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef TGradientImagePixelType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GradientPixelType

Definition at line 145 of file itkDiffusionTensor3DReconstructionImageFilter.h.

typedef InputImageType::ConstPointer itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputImageConstPointer [inherited]

Definition at line 83 of file itkImageToImageFilter.h.

typedef InputImageType::PixelType itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputImagePixelType [inherited]

Definition at line 85 of file itkImageToImageFilter.h.

typedef InputImageType::Pointer itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputImagePointer [inherited]

Definition at line 82 of file itkImageToImageFilter.h.

typedef InputImageType::RegionType itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputImageRegionType [inherited]

Definition at line 84 of file itkImageToImageFilter.h.

typedef Image< TReferenceImagePixelType, 3 > itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputImageType [inherited]

Some convenient typedefs. Definition at line 81 of file itkImageToImageFilter.h.

typedef ImageToImageFilterDetail::ImageRegionCopier<itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension) itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::InputToOutputRegionCopierType) [protected, inherited]

Typedef for the region copier function object that converts an input region to an output region. Definition at line 163 of file itkImageToImageFilter.h.

typedef OutputImageType::PixelType itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::OutputImagePixelType [inherited]

Definition at line 71 of file itkImageSource.h.

typedef OutputImageType::Pointer itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::OutputImagePointer [inherited]

Definition at line 69 of file itkImageSource.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef Superclass::OutputImageRegionType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::OutputImageRegionType

Superclass typedefs. Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 158 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef TensorImageType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::OutputImageType

Some convenient typedefs. Reimplemented from itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 155 of file itkDiffusionTensor3DReconstructionImageFilter.h.

typedef ImageToImageFilterDetail::ImageRegionCopier<itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension) itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::OutputToInputRegionCopierType) [protected, inherited]

Typedef for the region copier function object that converts an output region to an input region. Definition at line 168 of file itkImageToImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef SmartPointer<Self> itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::Pointer

Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 130 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef Superclass::InputImageType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::ReferenceImageType

Reference image data, This image is aquired in the absence of a diffusion sensitizing field gradient Definition at line 151 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef TReferenceImagePixelType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::ReferencePixelType

Definition at line 141 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef DiffusionTensor3DReconstructionImageFilter itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::Self

Standard class typedefs. Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 129 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef ImageToImageFilter< Image< TReferenceImagePixelType, 3>, Image< DiffusionTensor3D< TTensorPixelType >, 3 > > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::Superclass

Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >. Definition at line 134 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef vnl_matrix_fixed< double, 6, 6 > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::TensorBasisMatrixType

Holds the tensor basis coefficients G_k Definition at line 170 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef Image< TensorPixelType, 3 > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::TensorImageType

Definition at line 153 of file itkDiffusionTensor3DReconstructionImageFilter.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> typedef DiffusionTensor3D< TTensorPixelType > itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::TensorPixelType

Definition at line 147 of file itkDiffusionTensor3DReconstructionImageFilter.h.

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Member Enumeration Documentation

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> enum itk::DiffusionTensor3DReconstructionImageFilter::GradientImageTypeEnumeration [protected]

enum to indicate if the gradient image is specified as a single multi- component image or as several separate images Enumeration values: GradientIsInASingleImage  GradientIsInManyImages  Else  Definition at line 278 of file itkDiffusionTensor3DReconstructionImageFilter.h.

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Constructor & Destructor Documentation

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::DiffusionTensor3DReconstructionImageFilter (   )  [protected]

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::~DiffusionTensor3DReconstructionImageFilter (   )  [inline, protected]

Definition at line 267 of file itkDiffusionTensor3DReconstructionImageFilter.h.

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Member Function Documentation

virtual void itk::ProcessObject::AbortGenerateDataOff (   )  [virtual, inherited]

virtual void itk::ProcessObject::AbortGenerateDataOn (   )  [virtual, inherited]

Turn on and off the AbortGenerateData flag.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::AddGradientImage (  const GradientDirectionType &  , const GradientImageType *  image )

Set method to add a gradient direction and its corresponding image.

virtual void itk::ProcessObject::AddInput (  DataObject *  input  )  [protected, virtual, inherited]

virtual void itk::ProcessObject::AddOutput (  DataObject *  output  )  [protected, virtual, inherited]

virtual void itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::AfterThreadedGenerateData (   )  [inline, protected, virtual, inherited]

If an imaging filter needs to perform processing after all processing threads have completed, the filter can can provide an implementation for AfterThreadedGenerateData(). The execution flow in the default GenerateData() method will be: 1) Allocate the output buffer 2) Call BeforeThreadedGenerateData() 3) Spawn threads, calling ThreadedGenerateData() in each thread. 4) Call AfterThreadedGenerateData() Note that this flow of control is only available if a filter provides a ThreadedGenerateData() method and NOT a GenerateData() method. Definition at line 254 of file itkImageSource.h.

virtual void itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::AllocateOutputs (   )  [protected, virtual, inherited]

The GenerateData method normally allocates the buffers for all of the outputs of a filter. Some filters may want to override this default behavior. For example, a filter may have multiple outputs with varying resolution. Or a filter may want to process data in place by grafting its input to its output.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::BeforeThreadedGenerateData (  void   )  [protected, virtual]

If an imaging filter needs to perform processing after the buffer has been allocated but before threads are spawned, the filter can can provide an implementation for BeforeThreadedGenerateData(). The execution flow in the default GenerateData() method will be: 1) Allocate the output buffer 2) Call BeforeThreadedGenerateData() 3) Spawn threads, calling ThreadedGenerateData() in each thread. 4) Call AfterThreadedGenerateData() Note that this flow of control is only available if a filter provides a ThreadedGenerateData() method and NOT a GenerateData() method. Reimplemented from itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >.

static void itk::LightObject::BreakOnError (   )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual void itk::ProcessObject::CacheInputReleaseDataFlags (   )  [protected, virtual, inherited]

Cache the state of any ReleaseDataFlag's on the inputs. While the filter is executing, we need to set the ReleaseDataFlag's on the inputs to false in case the current filter is implemented using a mini-pipeline (which will try to release the inputs). After the filter finishes, we restore the state of the ReleaseDataFlag's before the call to ReleaseInputs().

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::CallCopyInputRegionToOutputRegion (  OutputImageRegionType &  destRegion, const InputImageRegionType &  srcRegion )  [protected, virtual, inherited]

This function calls the actual region copier to do the mapping from input image space to output image space. It uses a Function object used for dispatching to various routines to copy an input region (start index and size) to an output region. For most filters, this is a trivial copy because most filters require the input dimension to match the output dimension. However, some filters like itk::UnaryFunctorImageFilter can support output images of a higher dimension that the input. This function object is used by the default implementation of GenerateOutputInformation(). It can also be used in routines like ThreadedGenerateData() where a filter may need to map an input region to an output region. The default copier uses a "dispatch pattern" to call one of three overloaded functions depending on whether the input and output images are the same dimension, the input is a higher dimension that the output, or the input is of a lower dimension than the output. The use of an overloaded function is required for proper compilation of the various cases. For the latter two cases, trivial implementations are used. If the input image is a higher dimension than the output, the first portion of the input region is copied to the output region. If the input region is a lower dimension than the output, the input region information is copied into the first portion of the output region and the rest of the output region is set to zero. If a filter needs a different default behavior, it can override this method.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::CallCopyOutputRegionToInputRegion (  InputImageRegionType &  destRegion, const OutputImageRegionType &  srcRegion )  [protected, virtual, inherited]

This function calls the actual region copier to do the mapping from output image space to input image space. It uses a Function object used for dispatching to various routines to copy an output region (start index and size) to an input region. For most filters, this is a trivial copy because most filters require the input dimension to match the output dimension. However, some filters like itk::ExtractImageFilter can support output images of a lower dimension that the input. This function object can be used by GenerateOutputInformation() to copy the input LargestPossibleRegion to the output LargestPossibleRegion and can also be used in GenerateData or ThreadedGenerateData() where a filter may need to map an output region to an input region. The default copier uses a "dispatch pattern" to call one of three overloaded functions depending on whether the input and output images are the same dimension, the input is a higher dimension that the output, or the input is of a lower dimension than the output. The use of an overloaded function is required for proper compilation of the various cases. For the latter two cases, trivial implementations are used. If the input image is a higher dimension than the output, the output region information is copied into the first portion of the input region and the rest of the input region is set to zero. If the input region is a lower dimension than the output, the first portion of the output region is copied to the input region. If a filter needs a different default behavior, it can override this method. The ExtractImageFilter overrides this function object so that if the input image is a higher dimension than the output image, the filter can control "where" in the input image the output subimage is extracted (as opposed to mapping to first few dimensions of the input).

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::ComputeTensorBasis (   )  [protected]

virtual LightObject::Pointer itk::Object::CreateAnother (   )  const [virtual, inherited]

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class. Reimplemented from itk::LightObject.

virtual void itk::Object::DebugOff (   )  const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn (   )  const [virtual, inherited]

Turn debugging output on.

virtual void itk::LightObject::Delete (   )  [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

virtual void itk::ProcessObject::EnlargeOutputRequestedRegion (  DataObject *   )  [inline, virtual, inherited]

Give the process object a chance to indictate that it will produce more output than it was requested to produce. For example, many imaging filters must compute the entire output at once or can only produce output in complete slices. Such filters cannot handle smaller requested regions. These filters must provide an implementation of this method, setting the output requested region to the size they will produce. By default, a process object does not modify the size of the output requested region. Reimplemented in itk::CurvatureFlowImageFilter< TInputImage, TOutputImage >, itk::ExtensionVelocitiesImageFilter< TLevelSet, TAuxValue, VAuxDimension >, itk::FastMarchingExtensionImageFilter< TLevelSet, TAuxValue, VAuxDimension, TSpeedImage >, itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >, itk::ImagePCAShapeModelEstimator< TInputImage, TOutputImage >, itk::IsoContourDistanceImageFilter< TInputImage, TOutputImage >, itk::IsolatedWatershedImageFilter< TInputImage, TOutputImage >, itk::KLMRegionGrowImageFilter< TInputImage, TOutputImage >, itk::MRFImageFilter< TInputImage, TClassifiedImage >, itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField >, itk::ReinitializeLevelSetImageFilter< TLevelSet >, itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage, TBinaryPriorImage >, itk::WatershedImageFilter< TInputImage >, itk::BlackTopHatImageFilter< TInputImage, TOutputImage, TKernel >, itk::BSplineDecompositionImageFilter< TInputImage, TOutputImage >, itk::ClosingByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >, itk::ConfidenceConnectedImageFilter< TInputImage, TOutputImage >, itk::ConnectedComponentImageFilter< TInputImage, TOutputImage, TMaskImage >, itk::ConnectedThresholdImageFilter< TInputImage, TOutputImage >, itk::ContourDirectedMeanDistanceImageFilter< TInputImage1, TInputImage2 >, itk::ContourMeanDistanceImageFilter< TInputImage1, TInputImage2 >, itk::DirectedHausdorffDistanceImageFilter< TInputImage1, TInputImage2 >, itk::DoubleThresholdImageFilter< TInputImage, TOutputImage >, itk::ExtractOrthogonalSwath2DImageFilter< TImage >, itk::GradientMagnitudeRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::GradientRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::GrayscaleConnectedClosingImageFilter< TInputImage, TOutputImage >, itk::GrayscaleConnectedOpeningImageFilter< TInputImage, TOutputImage >, itk::GrayscaleFillholeImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGeodesicDilateImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGeodesicErodeImageFilter< TInputImage, TOutputImage >, itk::GrayscaleGrindPeakImageFilter< TInputImage, TOutputImage >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::HausdorffDistanceImageFilter< TInputImage1, TInputImage2 >, itk::HConcaveImageFilter< TInputImage, TOutputImage >, itk::HConvexImageFilter< TInputImage, TOutputImage >, itk::HessianRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::HMaximaImageFilter< TInputImage, TOutputImage >, itk::HMinimaImageFilter< TInputImage, TOutputImage >, itk::HoughTransform2DCirclesImageFilter< TInputPixelType, TOutputPixelType >, itk::HoughTransform2DLinesImageFilter< TInputPixelType, TOutputPixelType >, itk::ImportImageFilter< TPixel, VImageDimension >, itk::IsolatedConnectedImageFilter< TInputImage, TOutputImage >, itk::LabelStatisticsImageFilter< TInputImage, TLabelImage >, itk::LaplacianRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::MinimumMaximumImageFilter< TInputImage >, itk::NeighborhoodConnectedImageFilter< TInputImage, TOutputImage >, itk::OpeningByReconstructionImageFilter< TInputImage, TOutputImage, TKernel >, itk::OrientImageFilter< TInputImage, TOutputImage >, itk::ReconstructionByDilationImageFilter< TInputImage, TOutputImage >, itk::ReconstructionByErosionImageFilter< TInputImage, TOutputImage >, itk::RecursiveSeparableImageFilter< TInputImage, TOutputImage >, itk::RegionOfInterestImageFilter< TInputImage, TOutputImage >, itk::SimilarityIndexImageFilter< TInputImage1, TInputImage2 >, itk::SmoothingRecursiveGaussianImageFilter< TInputImage, TOutputImage >, itk::StatisticsImageFilter< TInputImage >, itk::TobogganImageFilter< TInputImage >, itk::VectorConfidenceConnectedImageFilter< TInputImage, TOutputImage >, itk::WhiteTopHatImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageFileReader< TOutputImage, ConvertPixelTraits >, itk::ImageSeriesReader< TOutputImage >, and itk::VoronoiSegmentationImageFilterBase< TInputImage, TOutputImage >. Definition at line 222 of file itkProcessObject.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> * The BValue itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::f (  s/mm^  2  )

virtual void itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GenerateData (  void   )  [protected, virtual, inherited]

A version of GenerateData() specific for image processing filters. This implementation will split the processing across multiple threads. The buffer is allocated by this method. Then the BeforeThreadedGenerateData() method is called (if provided). Then, a series of threads are spawned each calling ThreadedGenerateData(). After all the threads have completed processing, the AfterThreadedGenerateData() method is called (if provided). If an image processing filter cannot be threaded, the filter should provide an implementation of GenerateData(). That implementation is responsible for allocating the output buffer. If a filter an be threaded, it should NOT provide a GenerateData() method but should provide a ThreadedGenerateData() instead. See also: ThreadedGenerateData() Reimplemented from itk::ProcessObject.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GenerateInputRequestedRegion (   )  [protected, virtual, inherited]

What is the input requested region that is required to produce the output requested region? The base assumption for image processing filters is that the input requested region can be set to match the output requested region. If a filter requires more input (for instance a filter that uses neighborhoods needs more input than output to avoid introducing artificial boundary conditions) or less input (for instance a magnify filter) will have to override this method. In doing so, it should call its superclass' implementation as its first step. Note that imaging filters operate differently than the classes to this point in the class hierachy. Up till now, the base assumption has been that the largest possible region will be requested of the input. This implementation of GenerateInputRequestedRegion() only processes the inputs that are a subclass of the ImageBase<InputImageDimension>. If an input is another type of DataObject (including an Image of a different dimension), they are skipped by this method. The subclasses of ImageToImageFilter are responsible for providing an implementation of GenerateInputRequestedRegion() when there are multiple inputs of different types. See also: ProcessObject::GenerateInputRequestedRegion(), ImageSource::GenerateInputRequestedRegion() Reimplemented from itk::ProcessObject.

virtual void itk::ProcessObject::GenerateOutputInformation (   )  [protected, virtual, inherited]

Generate the information decribing the output data. The default implementation of this method will copy information from the input to the output. A filter may override this method if its output will have different information than its input. For instance, a filter that shrinks an image will need to provide an implementation for this method that changes the spacing of the pixels. Such filters should call their superclass' implementation of this method prior to changing the information values they need (i.e. GenerateOutputInformation() should call Superclass::GenerateOutputInformation() prior to changing the information. Reimplemented in itk::BayesianClassifierInitializationImageFilter< TInputImage, TProbabilityPrecisionType >, itk::BinaryMask3DMeshSource< TInputImage, TOutputMesh >, itk::FastMarchingExtensionImageFilter< TLevelSet, TAuxValue, VAuxDimension, TSpeedImage >, itk::FastMarchingImageFilter< TLevelSet, TSpeedImage >, itk::FFTComplexConjugateToRealImageFilter< TPixel, Dimension >, itk::FFTRealToComplexConjugateImageFilter< TPixel, Dimension >, itk::MRFImageFilter< TInputImage, TClassifiedImage >, itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField >, itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >, itk::VoronoiDiagram2DGenerator< TCoordType >, itk::AccumulateImageFilter< TInputImage, TOutputImage >, itk::BinaryMaskToNarrowBandPointSetFilter< TInputImage, TOutputMesh >, itk::ChangeInformationImageFilter< TInputImage >, itk::CropImageFilter< TInputImage, TOutputImage >, itk::DeformationFieldSource< TOutputImage >, itk::ExpandImageFilter< TInputImage, TOutputImage >, itk::ExtractImageFilter< TInputImage, TOutputImage >, itk::ExtractOrthogonalSwath2DImageFilter< TImage >, itk::FlipImageFilter< TImage >, itk::GaussianImageSource< TOutputImage >, itk::GradientImageToBloxBoundaryPointImageFilter< TInputImage >, itk::HoughTransform2DLinesImageFilter< TInputPixelType, TOutputPixelType >, itk::ImageToMeshFilter< TInputImage, TOutputMesh >, itk::ImageToParametricSpaceFilter< TInputImage, TOutputMesh >, itk::ImportImageFilter< TPixel, VImageDimension >, itk::InterpolateImagePointsFilter< TInputImage, TOutputImage, TCoordType, InterpolatorType >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::JoinSeriesImageFilter< TInputImage, TOutputImage >, itk::NonThreadedShrinkImageFilter< TInputImage, TOutputImage >, itk::OrientImageFilter< TInputImage, TOutputImage >, itk::PadImageFilter< TInputImage, TOutputImage >, itk::ParametricSpaceToImageSpaceMeshFilter< TInputMesh, TOutputMesh >, itk::PathToImageFilter< TInputPath, TOutputImage >, itk::PermuteAxesImageFilter< TImage >, itk::PointSetToImageFilter< TInputPointSet, TOutputImage >, itk::RandomImageSource< TOutputImage >, itk::RegionOfInterestImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::ShrinkImageFilter< TInputImage, TOutputImage >, itk::SpatialObjectToImageFilter< TInputSpatialObject, TOutputImage >, itk::SpatialObjectToPointSetFilter< TInputSpatialObject, TOutputPointSet >, itk::TileImageFilter< TInputImage, TOutputImage >, itk::TriangleMeshToBinaryImageFilter, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, TFunction >, itk::VectorExpandImageFilter< TInputImage, TOutputImage >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VTKImageImport< TOutputImage >, itk::WarpImageFilter< TInputImage, TOutputImage, TDeformationField >, itk::WarpVectorImageFilter< TInputImage, TOutputImage, TDeformationField >, itk::ImageFileReader< TOutputImage, ConvertPixelTraits >, itk::ImageSeriesReader< TOutputImage >, itk::HistogramToImageFilter< THistogram, TFunction >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Atan< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Cos< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Acos< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::InvertIntensityTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ChangeLabel< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< FeatureImageType, ImageType, Functor::Cast< FeatureImageType::PixelType, ImageType::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Log< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Abs< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Exp< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToReal< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Cast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::BoundedReciprocal< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sigmoid< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorCast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorMagnitudeLinearTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::IntensityLinearTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToModulus< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::IntensityWindowingTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::NOT< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Tan< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ExpNegative< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToPhase< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ThresholdLabeler< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::SymmetricEigenAnalysisFunction< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sin< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::RGBToLuminance< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::TensorRelativeAnisotropyFunction< TInputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::MatrixIndexSelection< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Sqrt< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::BinaryThreshold< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Log10< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::AccessorFunctor< TInputImage::PixelType, TAccessor > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::ModulusTransform< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::TensorFractionalAnisotropyFunction< TInputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::Asin< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::EdgePotential< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::Square< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::VectorIndexSelectionCast< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Functor::GradientMagnitude< TInputImage::PixelType, TOutputImage::PixelType > >, itk::UnaryFunctorImageFilter< TInputImage, TOutputImage, Function::ComplexToImaginary< TInputImage::PixelType, TOutputImage::PixelType > >, itk::HistogramToImageFilter< THistogram, Function::HistogramEntropyFunction< unsigned long > >, itk::HistogramToImageFilter< THistogram, Function::HistogramLogProbabilityFunction< unsigned long > >, itk::HistogramToImageFilter< THistogram, Function::HistogramProbabilityFunction< unsigned long > >, and itk::HistogramToImageFilter< THistogram, Function::HistogramIntensityFunction< unsigned long > >.

virtual void itk::ProcessObject::GenerateOutputRequestedRegion (  DataObject *  output  )  [protected, virtual, inherited]

Given one output whose requested region has been set, how should the requested regions for the remaining outputs of the process object be set? By default, all the outputs are set to the same requested region. If a filter needs to produce different requested regions for each output, for instance an image processing filter producing several outputs at different resolutions, then that filter may override this method and set the requested regions appropriatedly. Note that a filter producing multiple outputs of different types is required to override this method. The default implementation can only correctly handle multiple outputs of the same type. Reimplemented in itk::MultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::RecursiveMultiResolutionPyramidImageFilter< TInputImage, TOutputImage >, itk::watershed::BoundaryResolver< TPixelType, TDimension >, itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >, itk::watershed::Relabeler< TScalarType, TImageDimension >, itk::watershed::Segmenter< TInputImage >, itk::watershed::SegmentTreeGenerator< TScalarType >, itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>, and itk::watershed::SegmentTreeGenerator< ScalarType >.

virtual const bool& itk::ProcessObject::GetAbortGenerateData (   )  [virtual, inherited]

Get the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> virtual const TTensorPixelType& itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GetBValue (   )  [virtual]

Command* itk::Object::GetCommand (  unsigned long  tag  )  [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

bool itk::Object::GetDebug (   )  const [inherited]

Get the value of the debug flag.

static bool itk::Object::GetGlobalWarningDisplay (   )  [static, inherited]

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> Return the gradient direction idx is based* virtual GradientDirectionType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GetGradientDirection (  unsigned int  idx  )  const [inline, virtual]

Definition at line 213 of file itkDiffusionTensor3DReconstructionImageFilter.h. References itkExceptionMacro.

const DataObject* itk::ProcessObject::GetInput (  unsigned int  idx  )  const [protected, inherited]

const InputImageType* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GetInput (  unsigned int  idx  )  [inherited]

Reimplemented from itk::ProcessObject.

const InputImageType* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GetInput (  void   )  [inherited]

DataObjectPointerArray& itk::ProcessObject::GetInputs (   )  [inline, inherited]

Return an array with all the inputs of this process object. This is useful for tracing back in the pipeline to construct graphs etc. Definition at line 108 of file itkProcessObject.h.

const MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  const [inherited]

Returns: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  [inherited]

Returns: A reference to this objects MetaDataDictionary. Warning: This reference may be changed.

virtual unsigned long itk::Object::GetMTime (   )  const [virtual, inherited]

Return this objects modified time. Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::SceneSpatialObject< SpaceDimension >, and itk::SceneSpatialObject< NDimensions >.

MultiThreader* itk::ProcessObject::GetMultiThreader (   )  [inline, inherited]

Return the multithreader used by this class. Definition at line 281 of file itkProcessObject.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> virtual const char* itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GetNameOfClass (   )  const [virtual]

Runtime information support. Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >.

std::vector<DataObjectPointer>::size_type itk::ProcessObject::GetNumberOfInputs (   )  const [inline, inherited]

Get the size of the input vector. This is merely the size of the input vector, not the number of inputs that have valid DataObject's assigned. Use GetNumberOfValidRequiredInputs() to determine how many inputs are non-null. Definition at line 115 of file itkProcessObject.h.

std::vector<DataObjectPointer>::size_type itk::ProcessObject::GetNumberOfOutputs (   )  const [inline, inherited]

Definition at line 132 of file itkProcessObject.h.

virtual const unsigned int& itk::ProcessObject::GetNumberOfRequiredInputs (   )  [protected, virtual, inherited]

virtual const unsigned int& itk::ProcessObject::GetNumberOfRequiredOutputs (   )  [protected, virtual, inherited]

virtual const int& itk::ProcessObject::GetNumberOfThreads (   )  [virtual, inherited]

virtual std::vector<DataObjectPointer>::size_type itk::ProcessObject::GetNumberOfValidRequiredInputs (   )  const [virtual, inherited]

Get the number of valid inputs. This is the number of non-null entries in the input vector in the first NumberOfRequiredInputs slots. This method is used to determine whether the necessary required inputs have been set. Subclasses of ProcessObject may override this implementation if the required inputs are not the first slots in input vector. Reimplemented in itk::MultiResolutionPDEDeformableRegistration< TFixedImage, TMovingImage, TDeformationField >, and itk::PDEDeformableRegistrationFilter< TFixedImage, TMovingImage, TDeformationField >.

const DataObject* itk::ProcessObject::GetOutput (  unsigned int  idx  )  const [protected, inherited]

OutputImageType* itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GetOutput (  unsigned int  idx  )  [inherited]

Reimplemented from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GetOutput (  void   )  [inherited]

Return an array with all the outputs of this process object* This is useful for tracing forward in the pipeline to contruct* graphs etc* DataObjectPointerArray& itk::ProcessObject::GetOutputs (   )  [inline, inherited]

Definition at line 130 of file itkProcessObject.h.

virtual const float& itk::ProcessObject::GetProgress (   )  [virtual, inherited]

Get the execution progress of a process object. The progress is a floating number in [0,1] with 0 meaning no progress and 1 meaning the filter has completed execution.

virtual int itk::LightObject::GetReferenceCount (   )  const [inline, virtual, inherited]

Gets the reference count on this object. Definition at line 98 of file itkLightObject.h.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> virtual ReferenceImageType* itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GetReferenceImage (   )  [inline, virtual]

Get reference image Definition at line 209 of file itkDiffusionTensor3DReconstructionImageFilter.h. References itk::fem::this.

virtual const bool& itk::ProcessObject::GetReleaseDataBeforeUpdateFlag (   )  [virtual, inherited]

virtual bool itk::ProcessObject::GetReleaseDataFlag (   )  const [virtual, inherited]

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> virtual ReferencePixelType itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::GetThreshold (   )  [virtual]

static void itk::Object::GlobalWarningDisplayOff (   )  [inline, static, inherited]

Definition at line 100 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (   )  [inline, static, inherited]

Definition at line 98 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

virtual void itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GraftNthOutput (  unsigned int  idx, DataObject *  output )  [virtual, inherited]

Graft the specified data object onto this ProcessObject's idx'th output. This is the similar to GraftOutput method except is allows you specify which output is affected. The specified index must be a valid output number (less than ProcessObject::GetNumberOfOutputs()). See the GraftOutput for general usage information.

virtual void itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::GraftOutput (  DataObject *  output  )  [virtual, inherited]

Graft the specified DataObject onto this ProcessObject's output. This method grabs a handle to the specified DataObject's bulk data to used as its output's own bulk data. It also copies the region ivars (RequestedRegion, BufferedRegion, LargestPossibleRegion) and meta-data (Spacing, Origin) from the specified data object into this filter's output data object. Most importantly, however, it leaves the Source ivar untouched so the original pipeline routing is intact. This method is used when a process object is implemented using a mini-pipeline which is defined in its GenerateData() method. The usage is: // setup the mini-pipeline to process the input to this filter firstFilterInMiniPipeline->SetInput( this->GetInput() ); // setup the mini-pipeline to calculate the correct regions // and write to the appropriate bulk data block lastFilterInMiniPipeline->GraftOutput( this->GetOutput() ); // execute the mini-pipeline lastFilterInMiniPipeline->Update(); // graft the mini-pipeline output back onto this filter's output. // this is needed to get the appropriate regions passed back. this->GraftOutput( lastFilterInMiniPipeline->GetOutput() ); For proper pipeline execution, a filter using a mini-pipeline must implement the GenerateInputRequestedRegion(), GenerateOutputRequestedRegion(), GenerateOutputInformation() and EnlargeOutputRequestedRegion() methods as necessary to reflect how the mini-pipeline will execute (in other words, the outer filter's pipeline mechanism must be consistent with what the mini-pipeline will do).

bool itk::Object::HasObserver (  const EventObject &  event  )  const [inherited]

Return true if an observer is registered for this event.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* a image is a pointer to some Image and the* particular ProcessObjects involved are filters The same* examples apply to non itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::image (  e.g.  Mesh  )  [inherited]

itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::ImageSource (   )  [protected, inherited]

itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::ImageToImageFilter (   )  [protected, inherited]

void itk::Object::InvokeEvent (  const EventObject &   )  const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

void itk::Object::InvokeEvent (  const EventObject &   )  [inherited]

Call Execute on all the Commands observing this event id.

itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::itkStaticConstMacro (  OutputImageDimension  , unsigned  int, Image< DiffusionTensor3D< TTensorPixelType >, 3 > ::ImageDimension  )  [inherited]

ImageDimension constants* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::itkStaticConstMacro (  InputImageDimension  , unsigned  int, Image< TReferenceImagePixelType, 3 > ::ImageDimension  )  [inherited]

virtual DataObjectPointer itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::MakeOutput (  unsigned int  idx  )  [virtual, inherited]

Make a DataObject of the correct type to used as the specified output. Every ProcessObject subclass must be able to create a DataObject that can be used as a specified output. This method is automatically called when DataObject::DisconnectPipeline() is called. DataObject::DisconnectPipeline, disconnects a data object from being an output of its current source. When the data object is disconnected, the ProcessObject needs to construct a replacement output data object so that the ProcessObject is in a valid state. So DataObject::DisconnectPipeline eventually calls ProcessObject::MakeOutput. Note that MakeOutput always returns a SmartPointer to a DataObject. If a subclass of ImageSource has multiple outputs of different types, then that class must provide an implementation of MakeOutput(). Reimplemented from itk::ProcessObject.

virtual void itk::Object::Modified (   )  const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data. Referenced by itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> static Pointer itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::New (   )  [static]

Method for creation through the object factory. Reimplemented from itk::Object.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PopBackInput (   )  [virtual, inherited]

Reimplemented from itk::ProcessObject.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PopFrontInput (   )  [virtual, inherited]

Reimplemented from itk::ProcessObject.

virtual void itk::ProcessObject::PrepareOutputs (   )  [virtual, inherited]

An opportunity to deallocate a ProcessObject's bulk data storage. Some filters may wish to reuse existing bulk data storage to avoid unnecessary deallocation/allocation sequences. The default implementation calls Initialize() on each output. DataObject::Initialize() frees its bulk data by default. Reimplemented in itk::WatershedImageFilter< TInputImage >.

void itk::LightObject::Print (  std::ostream &  os, Indent  indent = 0 )  const [inherited]

Cause the object to print itself out.

bool itk::Object::PrintObservers (  std::ostream &  os, Indent  indent )  const [protected, inherited]

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::PrintSelf (  std::ostream &  os, Indent  indent )  const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes. Reimplemented from itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 >, Image< DiffusionTensor3D< TTensorPixelType >, 3 > >.

virtual void itk::LightObject::PrintTrailer (  std::ostream &  os, Indent  indent )  const [protected, virtual, inherited]

virtual void itk::ProcessObject::PropagateRequestedRegion (  DataObject *  output  )  [virtual, inherited]

Send the requested region information back up the pipeline (to the filters that preceed this one). Reimplemented in itk::VTKImageImport< TOutputImage >.

virtual void itk::ProcessObject::PropagateResetPipeline (   )  [protected, virtual, inherited]

Propagate a call to ResetPipeline() up the pipeline. Called only from DataObject.

* * these methods end of hiding the versions from the superclass* ProcessObject whose arguments are DataObjects we re expose* the versions from ProcessObject to avoid warnings about hiding* methods from the superclass* void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushBackInput (  const DataObject *  input  )  [inline, protected, virtual, inherited]

Reimplemented from itk::ProcessObject. Definition at line 250 of file itkImageToImageFilter.h.

* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushBackInput (   )  [protected, inherited]

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on then* run the filter on then run the filter on the application can accomplish this by popping* an input off the front of the input list and push a new image* onto the back of input list this only makes sense for* filters that single type of input* * Other uses are also possible For a single input pushing* and popping inputs allow the application to temporarily replace* an input to a filter** virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushBackInput (  const InputImageType *  image  )  [virtual, inherited]

* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushFronInput (   )  [protected, inherited]

void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushFrontInput (  const DataObject *  input  )  [inline, protected, virtual, inherited]

Reimplemented from itk::ProcessObject. Definition at line 252 of file itkImageToImageFilter.h.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::PushFrontInput (  const InputImageType *  image  )  [virtual, inherited]

virtual void itk::Object::Register (   )  const [virtual, inherited]

Increase the reference count (mark as used by another object). Reimplemented from itk::LightObject.

virtual void itk::ProcessObject::ReleaseDataBeforeUpdateFlagOff (   )  [virtual, inherited]

virtual void itk::ProcessObject::ReleaseDataBeforeUpdateFlagOn (   )  [virtual, inherited]

void itk::ProcessObject::ReleaseDataFlagOff (   )  [inline, inherited]

Definition at line 254 of file itkProcessObject.h.

void itk::ProcessObject::ReleaseDataFlagOn (   )  [inline, inherited]

Definition at line 253 of file itkProcessObject.h.

virtual void itk::ProcessObject::ReleaseInputs (   )  [protected, virtual, inherited]

A filter may need to release its input's bulk data after it has finished calculating a new output. The filter may need to release the inputs because the user has turned on the ReleaseDataFlag or it may need to release the inputs because the filter is an "in place" filter and it has overwritten its input with its output data. The implementation here simply checks the ReleaseDataFlag of the inputs. InPlaceImageFilter overrides this method so release the input it has overwritten. See also: InPlaceImageFilter::ReleaseInputs() Reimplemented in itk::InPlaceImageFilter< TInputImage, TOutputImage >, itk::InPlaceImageFilter< TInputImage, TOutputImage >, itk::InPlaceImageFilter< TDeformationField, TDeformationField >, itk::InPlaceImageFilter< TInputImage >, itk::InPlaceImageFilter< TInputImage, TSparseOutputImage >, itk::InPlaceImageFilter< TInputImage1, TOutputImage >, itk::InPlaceImageFilter< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >, itk::InPlaceImageFilter< FeatureImageType, ImageType >, itk::InPlaceImageFilter< TInputImage1, Functor::MakeJoin< TInputImage1, TInputImage2 >::ImageType >, itk::InPlaceImageFilter< TInputImageType, TSparseOutputImageType >, and itk::InPlaceImageFilter< TImage, TImage >.

void itk::Object::RemoveAllObservers (   )  [inherited]

Remove all observers .

virtual void itk::ProcessObject::RemoveInput (  DataObject *  input  )  [protected, virtual, inherited]

void itk::Object::RemoveObserver (  unsigned long  tag  )  [inherited]

Remove the observer with this tag value.

virtual void itk::ProcessObject::RemoveOutput (  DataObject *  output  )  [protected, virtual, inherited]

virtual void itk::ProcessObject::ResetPipeline (   )  [virtual, inherited]

Reset the pipeline. If an exception is thrown during an Update(), the pipeline may be in an inconsistent state. This method clears the internal state of the pipeline so Update() can be called.

virtual void itk::ProcessObject::RestoreInputReleaseDataFlags (   )  [protected, virtual, inherited]

Restore the cached input ReleaseDataFlags.

virtual void itk::ProcessObject::SetAbortGenerateData (  bool  _arg  )  [virtual, inherited]

Set the AbortGenerateData flag for the process object. Process objects may handle premature termination of execution in different ways.

void itk::Object::SetDebug (  bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

This is a global flag that controls whether any warning* or error messages are displayed* static void itk::Object::SetGlobalWarningDisplay (  bool  flag  )  [static, inherited]

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::SetGradientImage (  GradientDirectionContainerType *  , const GradientImagesType *  image )

Another set method to add a gradient directions and its corresponding image. The image here is a VectorImage. The user is expected to pass the gradient directions in a container. The ith element of the container corresponds to the gradient direction of the ith component image the VectorImage. For the baseline image, a vector of all zeros should be set.

virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::SetInput (  unsigned  int, const Image< TReferenceImagePixelType, 3 > *  image )  [virtual, inherited]

Set Get the image input of this process object* virtual void itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::SetInput (  const InputImageType *  image  )  [virtual, inherited]

void itk::Object::SetMetaDataDictionary (  const MetaDataDictionary &  rhs  )  [inherited]

Returns: Set the MetaDataDictionary

Protected methods for setting inputs* Subclasses make use of them for setting input* virtual void itk::ProcessObject::SetNthInput (  unsigned int  num, DataObject *  input )  [protected, virtual, inherited]

Referenced by itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetBoundaryA(), itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetBoundaryB(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetEquivalencyTable(), itk::WatershedImageFilter< TInputImage >::SetInput(), itk::watershed::SegmentTreeGenerator< ScalarType >::SetInputEquivalencyTable(), itk::watershed::Segmenter< TInputImage >::SetInputImage(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetInputImage(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetInputImage(), itk::watershed::SegmentTreeGenerator< ScalarType >::SetInputSegmentTable(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetInputSegmentTree(), itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >::SetReferenceImage(), itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::SetReferenceImage(), and itk::ChangeInformationImageFilter< TInputImage >::SetReferenceImage().

Protected methods for setting outputs* Subclasses make use of them for getting output* virtual void itk::ProcessObject::SetNthOutput (  unsigned int  num, DataObject *  output )  [protected, virtual, inherited]

Referenced by itk::watershed::BoundaryResolver< TPixelType, TDimension >::BoundaryResolver(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::EquivalenceRelabeler(), itk::watershed::Segmenter< TInputImage >::SetBoundary(), itk::watershed::BoundaryResolver< TPixelType, TDimension >::SetEquivalencyTable(), itk::watershed::Segmenter< TInputImage >::SetOutputImage(), itk::watershed::Relabeler< ScalarType, itkGetStaticConstMacro(ImageDimension)>::SetOutputImage(), itk::watershed::EquivalenceRelabeler< TScalarType, TImageDimension >::SetOutputImage(), and itk::watershed::Segmenter< TInputImage >::SetSegmentTable().

void itk::ProcessObject::SetNumberOfInputs (  unsigned int  num  )  [protected, inherited]

Called to allocate the input array. Copies old inputs.

void itk::ProcessObject::SetNumberOfOutputs (  unsigned int  num  )  [protected, inherited]

Called to allocate the output array. Copies old outputs.

virtual void itk::ProcessObject::SetNumberOfRequiredInputs (  unsigned int  _arg  )  [protected, virtual, inherited]

virtual void itk::ProcessObject::SetNumberOfRequiredOutputs (  unsigned int  _arg  )  [protected, virtual, inherited]

Get Set the number of threads to create when executing* virtual void itk::ProcessObject::SetNumberOfThreads (  int  _arg  )  [virtual, inherited]

virtual void itk::ProcessObject::SetProgress (  float  _arg  )  [virtual, inherited]

Set the execution progress of a process object. The progress is a floating number in [0,1] with 0 meaning no progress and 1 meaning the filter has completed execution. The ProgressEvent is NOT invoked.

virtual void itk::Object::SetReferenceCount (  int   )  [virtual, inherited]

Sets the reference count (use with care) Reimplemented from itk::LightObject.

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::SetReferenceImage (  ReferenceImageType *  referenceImage  )  [inline]

Set method to set the reference image. Definition at line 195 of file itkDiffusionTensor3DReconstructionImageFilter.h. References itkExceptionMacro, and itk::ProcessObject::SetNthInput().

Turn on off the flags to control whether the bulk data belonging* to the outputs of this ProcessObject are released after being* used by a downstream ProcessObject Default value is off Another* options for controlling memory utilization is the* ReleaseDataBeforeUpdateFlag* virtual void itk::ProcessObject::SetReleaseDataFlag (  bool  flag  )  [virtual, inherited]

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> Threshold on the reference image data The output tensor will be a null* tensor for pixels in the reference image that have a value less than this* threshold* virtual void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::SetThreshold (  ReferencePixelType  _arg  )  [virtual]

virtual int itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::SplitRequestedRegion (  int  i, int  num, OutputImageRegionType &  splitRegion )  [protected, virtual, inherited]

Split the output's RequestedRegion into "num" pieces, returning region "i" as "splitRegion". This method is called "num" times. The regions must not overlap. The method returns the number of pieces that the routine is capable of splitting the output RequestedRegion, i.e. return value is less than or equal to "num".

template<class TReferenceImagePixelType, class TGradientImagePixelType = TReferenceImagePixelType, class TTensorPixelType = double> void itk::DiffusionTensor3DReconstructionImageFilter< TReferenceImagePixelType, TGradientImagePixelType, TTensorPixelType >::ThreadedGenerateData (  const OutputImageRegionType &  outputRegionForThread, int  )  [protected, virtual]

If an imaging filter can be implemented as a multithreaded algorithm, the filter will provide an implementation of ThreadedGenerateData(). This superclass will automatically split the output image into a number of pieces, spawn multiple threads, and call ThreadedGenerateData() in each thread. Prior to spawning threads, the BeforeThreadedGenerateData() method is called. After all the threads have completed, the AfterThreadedGenerateData() method is called. If an image processing filter cannot support threading, that filter should provide an implementation of the GenerateData() method instead of providing an implementation of ThreadedGenerateData(). If a filter provides a GenerateData() method as its implementation, then the filter is responsible for allocating the output data. If a filter provides a ThreadedGenerateData() method as its implementation, then the output memory will allocated automatically by this superclass. The ThreadedGenerateData() method should only produce the output specified by "outputThreadRegion" parameter. ThreadedGenerateData() cannot write to any other portion of the output image (as this is responsibility of a different thread). See also: GenerateData(), SplitRequestedRegion() Reimplemented from itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >.

static ITK_THREAD_RETURN_TYPE itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::ThreaderCallback (  void *  arg  )  [static, protected, inherited]

Static function used as a "callback" by the MultiThreader. The threading library will call this routine for each thread, which will delegate the control to ThreadedGenerateData().

virtual void itk::Object::UnRegister (   )  const [virtual, inherited]

Decrease the reference count (release by another object). Reimplemented from itk::LightObject.

* endcode* In the above the two lines of code can be in* either order* * Note that it may be more efficient to* use a pipeline than to call itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

* endcode* In the above the two lines of code can be in* either order* * Note that itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

* endcode* * code* someFilter itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

* image itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

* anotherFilter itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

Get the output data of this process object The output of this* function is not valid until an appropriate itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Update (   )  [virtual, inherited]

Bring this filter up-to-date. Update() checks modified times against last execution times, and re-executes objects if necessary. A side effect of this method is that the whole pipeline may execute in order to bring this filter up-to-date. This method updates the currently prescribed requested region. If no requested region has been set on the output, then the requested region will be set to the largest possible region. Once the requested region is set, Update() will make sure the specified requested region is up-to-date. This is a confusing side effect to users who are just calling Update() on a filter. A first call to Update() will cause the largest possible region to be updated. A second call to Update() will update that same region. If a modification to the upstream pipeline cause a filter to have a different largest possible region, this second call to Update() will not cause the output requested region to be reset to the new largest possible region. Instead, the output requested region will be the same as the last time Update() was called. To have a filter always to produce its largest possible region, users should call UpdateLargestPossibleRegion() instead. Reimplemented from itk::ProcessObject.

virtual void itk::ProcessObject::UpdateLargestPossibleRegion (   )  [virtual, inherited]

Like Update(), but sets the output requested region to the largest possible region for the output. This is the method users should call if they want the entire dataset to be processed. If a user wants to update the same output region as a previous call to Update() or a previous call to UpdateLargestPossibleRegion(), then they should call the method Update().

virtual void itk::ProcessObject::UpdateOutputData (  DataObject *  output  )  [virtual, inherited]

Actually generate new output Reimplemented in itk::StreamingImageFilter< TInputImage, TOutputImage >.

virtual void itk::ProcessObject::UpdateOutputInformation (   )  [virtual, inherited]

Update the information decribing the output data. This method transverses up the pipeline gathering modified time information. On the way back down the pipeline, this method calls GenerateOutputInformation() to set any necessary information about the output data objects. For instance, a filter that shrinks an image will need to provide an implementation for GenerateOutputInformation() that changes the spacing of the pixels. Such filters should call their superclass' implementation of GenerateOutputInformation prior to changing the information values they need (i.e. GenerateOutputInformation() should call Superclass::GenerateOutputInformation() prior to changing the information. Reimplemented in itk::watershed::Segmenter< TInputImage >, and itk::VTKImageImport< TOutputImage >.

void itk::ProcessObject::UpdateProgress (  float  amount  )  [inherited]

Update the progress of the process object. Sets the Progress ivar to amount and invokes any observers for the ProgressEvent. The parameter amount should be in [0,1] and is the cumulative (not incremental) progress.

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Member Data Documentation

Allow people to add remove invoke observers (callbacks) to any ITK * object. This is an implementation of the subject/observer design * pattern. An observer is added by specifying an event to respond to * and an itk unsigned lon itk::Object::AddObserver)(const EventObject &event, Command *) const [inherited]

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on then* run the filter on then run the filter on the application can accomplish this by popping* an input off the front of the input list and push a new image* onto the back of input list itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Again [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

This is a global flag that controls whether any itk::Object::debug [inherited]

Definition at line 94 of file itkObject.h.

* endcode* In the above itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::example [inherited]

Definition at line 100 of file itkImageSource.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on then* run the filter on then run the filter on the application can accomplish this by popping* an input off the front of the input list and push a new image* onto the back of input list this only makes sense for* filters that single type of input* * Other uses are also possible For a single input itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::filter [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::filters [inherited]

Reimplemented from itk::ProcessObject. Definition at line 103 of file itkImageToImageFilter.h.

* * these methods end of hiding the versions from the superclass* ProcessObject whose arguments are DataObjects itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Here [protected, inherited]

Definition at line 246 of file itkImageToImageFilter.h.

* itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::image [inherited]

Definition at line 98 of file itkImageSource.h.

* endcode* * In this a someFilter and a anotherFilter are said* to constitute a b pipeline* * code* itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::image [inherited]

Definition at line 92 of file itkImageSource.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on then* run the filter on then run the filter on* itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on then* run the filter on itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For if an application has* images and they need to run a filter on itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::images [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

Push Pop the input of this process object These methods allow a* filter to model its input vector as a queue or stack These* routines may not be appropriate for all especially* filters with different types of inputs These routines follow* the semantics of STL* * The routines are useful for applications that need to process* rolling sets of images For itk::ImageToImageFilter< Image< TReferenceImagePixelType, 3 > , Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::instance [inherited]

Definition at line 103 of file itkImageToImageFilter.h.

TimeStamp itk::ProcessObject::m_OutputInformationMTime [protected, inherited]

Time when GenerateOutputInformation was last called. Definition at line 428 of file itkProcessObject.h.

int itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects. Definition at line 119 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count Definition at line 122 of file itkLightObject.h.

bool itk::ProcessObject::m_Updating [protected, inherited]

This flag indicates when the pipeline is executing. It prevents infinite recursion when pipelines have loops. Definition at line 425 of file itkProcessObject.h.

Get the output data of this process object The output of this* function is not valid until an appropriate either explicitly or implicitly Both the filter* itself and the data object have and both* methods update the data Here are three ways to use* a image is a pointer to some Image itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::object [inherited]

Definition at line 79 of file itkImageSource.h.

Methods invoked by virtual Print () to print information about the object * including superclasses. Typically not called by the user (use Print() * instead) but used in the hierarchical print process to combine the * output of several classes. */ virtual void PrintSelf(std voi itk::LightObject::PrintHeader)(std::ostream &os, Indent indent) const [protected, inherited]

* endcode* In the above the two lines of code can be in* either order* * Note that it may be more efficient to* use a pipeline than to call the data generated is for the requested* itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::Region [inherited]

Definition at line 110 of file itkImageSource.h.

* endcode* * In this itk::ImageSource< Image< DiffusionTensor3D< TTensorPixelType >, 3 > >::situation [inherited]

Definition at line 88 of file itkImageSource.h.

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The documentation for this class was generated from the following file:

• itkDiffusionTensor3DReconstructionImageFilter.h

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