ITK
4.1.0
Insight Segmentation and Registration Toolkit
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#include <itkHessianToObjectnessMeasureImageFilter.h>
A filter to enhance M-dimensional objects in N-dimensional images.
The objectness measure is a generalization of Frangi's vesselness measure, which is based on the analysis of the the Hessian eigen system. The filter can enhance blob-like structures (M=0), vessel-like structures (M=1), 2D plate-like structures (M=2), hyper-plate-like structures (M=3) in N-dimensional images, with M<N. The filter takes an image of a Hessian pixels ( SymmetricSecondRankTensor pixels pixels ) and produces an enhanced image. The Hessian input image can be produced using itk::HessianRecursiveGaussianImageFilter.
Additional information can be from in the Insight Journal: http://hdl.handle.net/1926/576
Definition at line 62 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef SmartPointer< const Self > itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::ConstPointer |
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 72 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef itk::FixedArray< EigenValueType, itkGetStaticConstMacro(ImageDimension) > itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::EigenValueArrayType |
Definition at line 84 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::EigenValueType |
Definition at line 83 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef Superclass::InputImageType itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::InputImageType |
Some convenient typedefs.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 74 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef InputImageType::PixelType itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::InputPixelType |
Definition at line 76 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef OutputImageType::RegionType itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::OutputImageRegionType |
Superclass typedefs.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 78 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef Superclass::OutputImageType itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::OutputImageType |
Some convenient typedefs.
Reimplemented from itk::ImageSource< TOutputImage >.
Definition at line 75 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef OutputImageType::PixelType itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::OutputPixelType |
Definition at line 77 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef SmartPointer< Self > itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::Pointer |
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 71 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef HessianToObjectnessMeasureImageFilter itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::Self |
Standard class typedefs.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 67 of file itkHessianToObjectnessMeasureImageFilter.h.
typedef ImageToImageFilter< TInputImage, TOutputImage > itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::Superclass |
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Definition at line 69 of file itkHessianToObjectnessMeasureImageFilter.h.
itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::HessianToObjectnessMeasureImageFilter | ( | ) | [protected] |
End concept checking
itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::~HessianToObjectnessMeasureImageFilter | ( | ) | [inline, protected] |
End concept checking
Definition at line 141 of file itkHessianToObjectnessMeasureImageFilter.h.
itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::HessianToObjectnessMeasureImageFilter | ( | const Self & | ) | [private] |
void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::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< TOutputImage >.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::BrightObjectOff | ( | ) | [virtual] |
Enhance bright structures on a dark background if true, the opposite if false.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::BrightObjectOn | ( | ) | [virtual] |
Enhance bright structures on a dark background if true, the opposite if false.
virtual::itk::LightObject::Pointer itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::CreateAnother | ( | void | ) | const [virtual] |
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.
virtual double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetAlpha | ( | ) | const [virtual] |
Set/Get Alpha, the weight corresponding to R_A (the ratio of the smallest eigenvalue that has to be large to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality.
virtual double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetBeta | ( | ) | const [virtual] |
Set/Get Beta, the weight corresponding to R_B (the ratio of the largest eigenvalue that has to be small to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality.
virtual bool itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetBrightObject | ( | ) | const [virtual] |
Enhance bright structures on a dark background if true, the opposite if false.
virtual double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetGamma | ( | ) | const [virtual] |
Set/Get Gamma, the weight corresponding to S (the Frobenius norm of the Hessian matrix, or second-order structureness)
virtual const char* itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetNameOfClass | ( | ) | const [virtual] |
Runtime information support.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
virtual unsigned int itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetObjectDimension | ( | ) | const [virtual] |
Set/Get the dimensionality of the object (0: points (blobs), 1: lines (vessels), 2: planes (plate-like structures), 3: hyper-planes. ObjectDimension must be smaller than ImageDimension.
virtual bool itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::GetScaleObjectnessMeasure | ( | ) | const [virtual] |
Toggle scaling the objectness measure with the magnitude of the largest absolute eigenvalue
static Pointer itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::New | ( | ) | [static] |
Method for creation through the object factory.
Reimplemented from itk::Object.
void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::operator= | ( | const Self & | ) | [private] |
PushBackInput(), PushFronInput() in the public section force the input to be the type expected by an ImageToImageFilter. However, these methods end of "hiding" the versions from the superclass (ProcessObject) whose arguments are DataObjects. Here, we re-expose the versions from ProcessObject to avoid warnings about hiding methods from the superclass.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::PrintSelf | ( | std::ostream & | os, |
Indent | indent | ||
) | const [protected, virtual] |
End concept checking
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::ScaleObjectnessMeasureOff | ( | ) | [virtual] |
Toggle scaling the objectness measure with the magnitude of the largest absolute eigenvalue
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::ScaleObjectnessMeasureOn | ( | ) | [virtual] |
Toggle scaling the objectness measure with the magnitude of the largest absolute eigenvalue
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetAlpha | ( | double | _arg | ) | [virtual] |
Set/Get Alpha, the weight corresponding to R_A (the ratio of the smallest eigenvalue that has to be large to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetBeta | ( | double | _arg | ) | [virtual] |
Set/Get Beta, the weight corresponding to R_B (the ratio of the largest eigenvalue that has to be small to the larger ones). Smaller values lead to increased sensitivity to the object dimensionality.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetBrightObject | ( | bool | _arg | ) | [virtual] |
Enhance bright structures on a dark background if true, the opposite if false.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetGamma | ( | double | _arg | ) | [virtual] |
Set/Get Gamma, the weight corresponding to S (the Frobenius norm of the Hessian matrix, or second-order structureness)
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetObjectDimension | ( | unsigned int | _arg | ) | [virtual] |
Set/Get the dimensionality of the object (0: points (blobs), 1: lines (vessels), 2: planes (plate-like structures), 3: hyper-planes. ObjectDimension must be smaller than ImageDimension.
virtual void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::SetScaleObjectnessMeasure | ( | bool | _arg | ) | [virtual] |
Toggle scaling the objectness measure with the magnitude of the largest absolute eigenvalue
void itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::ThreadedGenerateData | ( | const OutputImageRegionType & | outputRegionForThread, |
ThreadIdType | threadId | ||
) | [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).
Reimplemented from itk::ImageSource< TOutputImage >.
itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::typedef | ( | Concept::Convertible< double, OutputPixelType > | ) |
Begin concept checking This class requires DoubleConvertibleToOutputCheck in the form of ( Concept::Convertible< double, OutputPixelType > )
const unsigned int itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::ImageDimension = ::itk::GetImageDimension< InputImageType >::ImageDimension [static] |
Image dimension
Definition at line 81 of file itkHessianToObjectnessMeasureImageFilter.h.
double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_Alpha [private] |
Definition at line 168 of file itkHessianToObjectnessMeasureImageFilter.h.
double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_Beta [private] |
Definition at line 169 of file itkHessianToObjectnessMeasureImageFilter.h.
bool itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_BrightObject [private] |
Definition at line 172 of file itkHessianToObjectnessMeasureImageFilter.h.
double itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_Gamma [private] |
Definition at line 170 of file itkHessianToObjectnessMeasureImageFilter.h.
unsigned int itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_ObjectDimension [private] |
Definition at line 171 of file itkHessianToObjectnessMeasureImageFilter.h.
bool itk::HessianToObjectnessMeasureImageFilter< TInputImage, TOutputImage >::m_ScaleObjectnessMeasure [private] |
Definition at line 173 of file itkHessianToObjectnessMeasureImageFilter.h.