ITK
5.2.0
Insight Toolkit
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#include <itkSTAPLEImageFilter.h>
Public Types | |
using | ConstPointer = SmartPointer< const Self > |
using | InputImagePointer = typename InputImageType::Pointer |
using | InputImageType = TInputImage |
using | InputPixelType = typename TInputImage::PixelType |
using | OutputImagePointer = typename OutputImageType::Pointer |
using | OutputImageRegionType = typename Superclass::OutputImageRegionType |
using | OutputImageType = TOutputImage |
using | OutputPixelType = typename TOutputImage::PixelType |
using | Pointer = SmartPointer< Self > |
using | RealType = typename NumericTraits< InputPixelType >::RealType |
using | Self = STAPLEImageFilter |
using | Superclass = ImageToImageFilter< TInputImage, TOutputImage > |
Public Types inherited from itk::ImageToImageFilter< TInputImage, TOutputImage > | |
using | ConstPointer = SmartPointer< const Self > |
using | InputImageConstPointer = typename InputImageType::ConstPointer |
using | InputImagePixelType = typename InputImageType::PixelType |
using | InputImagePointer = typename InputImageType::Pointer |
using | InputImageRegionType = typename InputImageType::RegionType |
using | InputImageType = TInputImage |
using | OutputImagePixelType = typename Superclass::OutputImagePixelType |
using | OutputImageRegionType = typename Superclass::OutputImageRegionType |
using | Pointer = SmartPointer< Self > |
using | Self = ImageToImageFilter |
using | Superclass = ImageSource< TOutputImage > |
Public Types inherited from itk::ImageSource< TOutputImage > | |
using | ConstPointer = SmartPointer< const Self > |
using | DataObjectIdentifierType = Superclass::DataObjectIdentifierType |
using | DataObjectPointer = DataObject::Pointer |
using | DataObjectPointerArraySizeType = Superclass::DataObjectPointerArraySizeType |
using | OutputImagePixelType = typename OutputImageType::PixelType |
using | OutputImagePointer = typename OutputImageType::Pointer |
using | OutputImageRegionType = typename OutputImageType::RegionType |
using | OutputImageType = TOutputImage |
using | Pointer = SmartPointer< Self > |
using | Self = ImageSource |
using | Superclass = ProcessObject |
Public Types inherited from itk::ProcessObject | |
using | ConstPointer = SmartPointer< const Self > |
using | DataObjectIdentifierType = DataObject::DataObjectIdentifierType |
using | DataObjectPointer = DataObject::Pointer |
using | DataObjectPointerArray = std::vector< DataObjectPointer > |
using | DataObjectPointerArraySizeType = DataObjectPointerArray::size_type |
using | MultiThreaderType = MultiThreaderBase |
using | NameArray = std::vector< DataObjectIdentifierType > |
using | Pointer = SmartPointer< Self > |
using | Self = ProcessObject |
using | Superclass = Object |
Public Types inherited from itk::Object | |
using | ConstPointer = SmartPointer< const Self > |
using | Pointer = SmartPointer< Self > |
using | Self = Object |
using | Superclass = LightObject |
Public Types inherited from itk::LightObject | |
using | ConstPointer = SmartPointer< const Self > |
using | Pointer = SmartPointer< Self > |
using | Self = LightObject |
Static Public Member Functions | |
static Pointer | New () |
Static Public Member Functions inherited from itk::ImageToImageFilter< TInputImage, TOutputImage > | |
static void | SetGlobalDefaultDirectionTolerance (double) |
static double | GetGlobalDefaultDirectionTolerance () |
static void | SetGlobalDefaultCoordinateTolerance (double) |
static double | GetGlobalDefaultCoordinateTolerance () |
Static Public Member Functions inherited from itk::Object | |
static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool val) |
Static Public Member Functions inherited from itk::LightObject | |
static void | BreakOnError () |
static Pointer | New () |
Static Public Attributes | |
static constexpr unsigned int | ImageDimension = TOutputImage::ImageDimension |
Static Public Attributes inherited from itk::ImageToImageFilter< TInputImage, TOutputImage > | |
static constexpr unsigned int | InputImageDimension = TInputImage::ImageDimension |
static constexpr unsigned int | OutputImageDimension = TOutputImage::ImageDimension |
Static Public Attributes inherited from itk::ImageSource< TOutputImage > | |
static constexpr unsigned int | OutputImageDimension = TOutputImage::ImageDimension |
InputPixelType | m_ForegroundValue |
unsigned int | m_ElapsedIterations |
unsigned int | m_MaximumIterations |
double | m_ConfidenceWeight |
std::vector< double > | m_Sensitivity |
std::vector< double > | m_Specificity |
virtual void | SetForegroundValue (InputPixelType _arg) |
virtual InputPixelType | GetForegroundValue () const |
const std::vector< double > & | GetSpecificity () const |
const std::vector< double > & | GetSensitivity () const |
double | GetSensitivity (unsigned int i) |
double | GetSpecificity (unsigned int i) |
virtual void | SetMaximumIterations (unsigned int _arg) |
virtual unsigned int | GetMaximumIterations () const |
virtual void | SetConfidenceWeight (double _arg) |
virtual double | GetConfidenceWeight () const |
virtual unsigned int | GetElapsedIterations () const |
STAPLEImageFilter () | |
~STAPLEImageFilter () override=default | |
void | GenerateData () override |
void | PrintSelf (std::ostream &, Indent) const override |
The STAPLE filter implements the Simultaneous Truth and Performance Level Estimation algorithm for generating ground truth volumes from a set of binary expert segmentations.
The STAPLE algorithm treats segmentation as a pixelwise classification, which leads to an averaging scheme that accounts for systematic biases in the behavior of experts in order to generate a fuzzy ground truth volume and simultaneous accuracy assessment of each expert. The ground truth volumes produced by this filter are floating point volumes of values between zero and one that indicate probability of each pixel being in the object targeted by the segmentation.
The STAPLE algorithm is described in
S. Warfield, K. Zou, W. Wells, "Validation of image segmentation and expert quality with an expectation-maximization algorithm" in MICCAI 2002: Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag, Heidelberg, Germany, 2002, pp. 298-306
Input volumes must all contain the same size RequestedRegions.
The SetConfidenceWeight parameter is a modifier for the prior probability that any pixel would be classified as inside the target object. This implementation of the STAPLE algorithm automatically calculates prior positive classification probability as the average fraction of the image volume filled by the target object in each input segmentation. The ConfidenceWeight parameter allows for scaling the of this default prior probability: if g_t is the prior probability that a pixel would be classified inside the target object, then g_t is set to g_t * ConfidenceWeight before iterating on the solution. In general ConfidenceWeight should be left to the default of 1.0.
You must provide a foreground value using SetForegroundValue that the STAPLE algorithm will use to identify positively classified pixels in the the input images. All other values in the image will be treated as background values. For example, if your input segmentations consist of 1's everywhere inside the segmented region, then use SetForegroundValue(1).
The STAPLE algorithm is an iterative E-M algorithm and will converge on a solution after some number of iterations that cannot be known a priori. After updating the filter, the total elapsed iterations taken to converge on the solution can be queried through GetElapsedIterations(). You may also specify a MaximumNumberOfIterations, after which the algorithm will stop iterating regardless of whether or not it has converged. This implementation of the STAPLE algorithm will find the solution to within seven digits of precision unless it is stopped early.
Once updated, the Sensitivity (true positive fraction, q) and Specificity (true negative fraction, q) for each expert input volume can be queried using GetSensitivity(i) and GetSpecificity(i), where i is the i-th input volume.
Definition at line 122 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::ConstPointer = SmartPointer<const Self> |
Definition at line 131 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::InputImagePointer = typename InputImageType::Pointer |
Definition at line 151 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::InputImageType = TInputImage |
Image type alias support
Definition at line 150 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::InputPixelType = typename TInputImage::PixelType |
Definition at line 142 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::OutputImagePointer = typename OutputImageType::Pointer |
Definition at line 153 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::OutputImageRegionType = typename Superclass::OutputImageRegionType |
Superclass type alias.
Definition at line 156 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::OutputImageType = TOutputImage |
Definition at line 152 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::OutputPixelType = typename TOutputImage::PixelType |
Extract some information from the image types. Dimensionality of the two images is assumed to be the same.
Definition at line 141 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::Pointer = SmartPointer<Self> |
Definition at line 130 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::RealType = typename NumericTraits<InputPixelType>::RealType |
Definition at line 143 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::Self = STAPLEImageFilter |
Standard class type aliases.
Definition at line 128 of file itkSTAPLEImageFilter.h.
using itk::STAPLEImageFilter< TInputImage, TOutputImage >::Superclass = ImageToImageFilter<TInputImage, TOutputImage> |
Definition at line 129 of file itkSTAPLEImageFilter.h.
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inlineprotected |
Set get the binary ON value of the input image.
Definition at line 235 of file itkSTAPLEImageFilter.h.
References itk::NumericTraits< T >::max(), and itk::NumericTraits< T >::OneValue().
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overrideprotecteddefault |
Set get the binary ON value of the input image.
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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.
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overrideprotectedvirtual |
Set get the binary ON value of the input image.
Reimplemented from itk::ImageSource< TOutputImage >.
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virtual |
Set get the binary ON value of the input image.
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Get the number of elapsed iterations of the iterative E-M algorithm.
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virtual |
Set get the binary ON value of the input image.
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Set get the binary ON value of the input image.
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Run-time type information (and related methods)
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
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inline |
After the filter is updated, this method returns a std::vector<double> of all Sensitivity (true positive fraction, p) values for the expert input volumes.
Definition at line 176 of file itkSTAPLEImageFilter.h.
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After the filter is updated, this method returns the Sensitivity (true positive fraction, p) value for the i-th expert input volume.
Definition at line 184 of file itkSTAPLEImageFilter.h.
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After the filter is updated, this method returns a std::vector<double> of all Specificity (true negative fraction, q) values for the expert input volumes.
Definition at line 167 of file itkSTAPLEImageFilter.h.
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inline |
After the filter is updated, this method returns the Specificity (true negative fraction, q) value for the i-th expert input volume.
Definition at line 197 of file itkSTAPLEImageFilter.h.
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static |
Method for creation through the object factory.
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overrideprotectedvirtual |
Set get the binary ON value of the input image.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
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virtual |
Scales the estimated prior probability that a pixel will be inside the targeted object of segmentation. The default prior probability g_t is calculated automatically as the average fraction of positively classified pixels to the total size of the volume (across all input volumes). ConfidenceWeight will scale this default value as g_t = g_t * ConfidenceWeight. In general, ConfidenceWeight should be left to the default of 1.0.
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Set get the binary ON value of the input image.
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Set/Get the maximum number of iterations after which the STAPLE algorithm will be considered to have converged. In general this SHOULD NOT be set and the algorithm should be allowed to converge on its own.
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staticconstexpr |
Extract some information from the image types. Dimensionality of the two images is assumed to be the same.
Definition at line 147 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 255 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 252 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 251 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 253 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 257 of file itkSTAPLEImageFilter.h.
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private |
Set get the binary ON value of the input image.
Definition at line 258 of file itkSTAPLEImageFilter.h.