ITK
4.13.0
Insight Segmentation and Registration Toolkit
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#include <itkBayesianClassifierImageFilter.h>
Performs Bayesian Classification on an image.
Definition at line 81 of file itkBayesianClassifierImageFilter.h.
Static Public Member Functions | |
static Pointer | New () |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool flag) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Static Public Attributes | |
static const unsigned int | Dimension = InputImageType ::ImageDimension |
Static Public Attributes inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > > | |
static const unsigned int | InputImageDimension |
static const unsigned int | OutputImageDimension |
Static Public Attributes inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > > | |
static const unsigned int | OutputImageDimension |
Private Attributes | |
unsigned int | m_NumberOfSmoothingIterations |
SmoothingFilterPointer | m_SmoothingFilter |
bool | m_UserProvidedPriors |
bool | m_UserProvidedSmoothingFilter |
Additional Inherited Members | |
Protected Types inherited from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > > | |
typedef ImageToImageFilterDetail::ImageRegionCopier < itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension) > | InputToOutputRegionCopierType |
typedef ImageToImageFilterDetail::ImageRegionCopier < itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension) > | OutputToInputRegionCopierType |
Static Protected Member Functions inherited from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > > | |
static const ImageRegionSplitterBase * | GetGlobalDefaultSplitter () |
static ITK_THREAD_RETURN_TYPE | ThreaderCallback (void *arg) |
Protected Attributes inherited from itk::ProcessObject | |
TimeStamp | m_OutputInformationMTime |
bool | m_Updating |
Protected Attributes inherited from itk::LightObject | |
AtomicInt< int > | m_ReferenceCount |
typedef SmartPointer< const Self > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ConstPointer |
Definition at line 94 of file itkBayesianClassifierImageFilter.h.
typedef Superclass::DataObjectPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DataObjectPointer |
Definition at line 155 of file itkBayesianClassifierImageFilter.h.
typedef ProcessObject::DataObjectPointerArraySizeType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DataObjectPointerArraySizeType |
This is overloaded to create the Posteriors output image.
Definition at line 179 of file itkBayesianClassifierImageFilter.h.
typedef DecisionRuleType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DecisionRulePointer |
Definition at line 153 of file itkBayesianClassifierImageFilter.h.
typedef Statistics::MaximumDecisionRule itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::DecisionRuleType |
Decision rule to use for defining the label.
Definition at line 152 of file itkBayesianClassifierImageFilter.h.
typedef itk::Image< TPosteriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ExtractedComponentImageType |
An image from a single component of the Posterior.
Definition at line 159 of file itkBayesianClassifierImageFilter.h.
typedef InputImageType::RegionType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::ImageRegionType |
Definition at line 113 of file itkBayesianClassifierImageFilter.h.
typedef ImageRegionConstIterator< InputImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImageIteratorType |
Input and Output image iterators.
Definition at line 116 of file itkBayesianClassifierImageFilter.h.
typedef InputImageType::ConstPointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImagePointer |
Definition at line 111 of file itkBayesianClassifierImageFilter.h.
typedef Superclass::InputImageType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputImageType |
Input and Output image types.
Definition at line 100 of file itkBayesianClassifierImageFilter.h.
typedef InputImageType::PixelType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::InputPixelType |
Pixel types.
Definition at line 120 of file itkBayesianClassifierImageFilter.h.
typedef ImageRegionConstIterator< MembershipImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImageIteratorType |
Definition at line 139 of file itkBayesianClassifierImageFilter.h.
typedef MembershipImageType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImagePointer |
Definition at line 138 of file itkBayesianClassifierImageFilter.h.
typedef TInputVectorImage itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipImageType |
Image Type and Pixel type for the images representing the membership of a pixel to a particular class. This image has arrays as pixels, the number of elements in the array is the same as the number of classes to be used.
Definition at line 136 of file itkBayesianClassifierImageFilter.h.
typedef MembershipImageType::PixelType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::MembershipPixelType |
Definition at line 137 of file itkBayesianClassifierImageFilter.h.
typedef ImageRegionIterator< OutputImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImageIteratorType |
Definition at line 117 of file itkBayesianClassifierImageFilter.h.
typedef OutputImageType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImagePointer |
Definition at line 112 of file itkBayesianClassifierImageFilter.h.
typedef Image< TLabelsType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputImageType |
Definition at line 110 of file itkBayesianClassifierImageFilter.h.
typedef OutputImageType::PixelType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::OutputPixelType |
Definition at line 121 of file itkBayesianClassifierImageFilter.h.
typedef SmartPointer< Self > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Pointer |
Definition at line 93 of file itkBayesianClassifierImageFilter.h.
typedef ImageRegionIterator< PosteriorsImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImageIteratorType |
Definition at line 149 of file itkBayesianClassifierImageFilter.h.
typedef PosteriorsImageType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImagePointer |
Definition at line 148 of file itkBayesianClassifierImageFilter.h.
typedef VectorImage< TPosteriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsImageType |
Image Type and Pixel type for the images representing the Posterior probability of a pixel belonging to a particular class. This image has arrays as pixels, the number of elements in the array is the same as the number of classes to be used.
Definition at line 146 of file itkBayesianClassifierImageFilter.h.
typedef PosteriorsImageType::PixelType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PosteriorsPixelType |
Definition at line 147 of file itkBayesianClassifierImageFilter.h.
typedef ImageRegionConstIterator< PriorsImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImageIteratorType |
Definition at line 131 of file itkBayesianClassifierImageFilter.h.
typedef PriorsImageType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImagePointer |
Definition at line 130 of file itkBayesianClassifierImageFilter.h.
typedef VectorImage< TPriorsPrecisionType, itkGetStaticConstMacro(Dimension) > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsImageType |
Image Type and Pixel type for the images representing the Prior probability of a pixel belonging to a particular class. This image has arrays as pixels, the number of elements in the array is the same as the number of classes to be used.
Definition at line 128 of file itkBayesianClassifierImageFilter.h.
typedef PriorsImageType::PixelType itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::PriorsPixelType |
Definition at line 129 of file itkBayesianClassifierImageFilter.h.
typedef BayesianClassifierImageFilter itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Self |
Standard class typedefs.
Definition at line 88 of file itkBayesianClassifierImageFilter.h.
typedef SmoothingFilterType::Pointer itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SmoothingFilterPointer |
Definition at line 166 of file itkBayesianClassifierImageFilter.h.
typedef ImageToImageFilter< ExtractedComponentImageType, ExtractedComponentImageType > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SmoothingFilterType |
Optional Smoothing filter that will be applied to the Posteriors.
Definition at line 164 of file itkBayesianClassifierImageFilter.h.
typedef ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > > itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::Superclass |
Definition at line 91 of file itkBayesianClassifierImageFilter.h.
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Definition at line 210 of file itkBayesianClassifierImageFilter.h.
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Compute the labeled map based on the Maximum rule applied to the posteriors.
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Compute the posteriors using the Bayes rule. If no priors are available, then the posteriors are just a copy of the memberships. Computes the labeled map for all combinations of conditions.
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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::Object.
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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.
Reimplemented from itk::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >.
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Generate the information describing 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 from itk::ProcessObject.
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Run-time type information (and related methods).
Reimplemented from itk::ImageToImageFilter< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >.
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Number of iterations to apply the smoothing filter.
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Get the Posteriors Image.
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Set/Get the smoothing filter that may optionally be applied to the posterior image.
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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::ImageSource< Image< TLabelsType, TInputVectorImage::ImageDimension > >.
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Method for creation through the object factory.
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Normalize the posteriors and smooth them using a user-provided.
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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< TInputVectorImage, Image< TLabelsType, TInputVectorImage::ImageDimension > >.
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Number of iterations to apply the smoothing filter.
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Set the priors image.
void itk::BayesianClassifierImageFilter< TInputVectorImage, TLabelsType, TPosteriorsPrecisionType, TPriorsPrecisionType >::SetSmoothingFilter | ( | SmoothingFilterType * | ) |
Set/Get the smoothing filter that may optionally be applied to the posterior image.
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Dimension of the input image.
Definition at line 107 of file itkBayesianClassifierImageFilter.h.
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Definition at line 242 of file itkBayesianClassifierImageFilter.h.
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Definition at line 240 of file itkBayesianClassifierImageFilter.h.
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Definition at line 233 of file itkBayesianClassifierImageFilter.h.
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Definition at line 238 of file itkBayesianClassifierImageFilter.h.