ITK
4.10.0
Insight Segmentation and Registration Toolkit
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#include <itkMultiLabelSTAPLEImageFilter.h>
This filter performs a pixelwise combination of an arbitrary number of input images, where each of them represents a segmentation of the same scene (i.e., image).
The labelings in the images are weighted relative to each other based on their "performance" as estimated by an expectation-maximization algorithm. In the process, a ground truth segmentation is estimated, and the estimated performances of the individual segmentations are relative to this estimated ground truth.
The algorithm is based on the binary STAPLE algorithm by Warfield et al. as published originally 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
The multi-label algorithm implemented here is described in detail in
T. Rohlfing, D. B. Russakoff, and C. R. Maurer, Jr., "Performance-based classifier combination in atlas-based image segmentation using expectation-maximization parameter estimation," IEEE Transactions on Medical Imaging, vol. 23, pp. 983-994, Aug. 2004.
Input volumes must all contain the same size RequestedRegions. Not all input images must contain all possible labels, but all label values must have the same meaning in all images.
The filter can optionally be provided with estimates for the a priori class probabilities through the SetPriorProbabilities function. If no estimate is provided, one is automatically generated by analyzing the relative frequencies of the labels in the input images.
By default, the label used for undecided pixels is the maximum label value used in the input images plus one. Since it is possible for an image with 8 bit pixel values to use all 256 possible label values, it is permissible to combine 8 bit (i.e., byte) images into a 16 bit (i.e., short) output image.
In addition to the combined image, the estimated confusion matrices for each of the input segmentations can be obtained through the GetConfusionMatrix member function.
A termination threshold for the EM iteration can be defined by calling SetTerminationUpdateThreshold. The iteration terminates once no single parameter of any confusion matrix changes by less than this threshold. Alternatively, a maximum number of iterations can be specified by calling SetMaximumNumberOfIterations. The algorithm may still terminate after a smaller number of iterations if the termination threshold criterion is satisfied.
Definition at line 118 of file itkMultiLabelSTAPLEImageFilter.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 | ImageDimension = TOutputImage::ImageDimension |
Static Public Attributes inherited from itk::ImageToImageFilter< TInputImage, TOutputImage > | |
static const unsigned int | InputImageDimension = TInputImage::ImageDimension |
static const unsigned int | OutputImageDimension = TOutputImage::ImageDimension |
Static Public Attributes inherited from itk::ImageSource< TOutputImage > | |
static const unsigned int | OutputImageDimension = TOutputImage::ImageDimension |
Private Member Functions | |
void | AllocateConfusionMatrixArray () |
void | InitializeConfusionMatrixArrayFromVoting () |
void | InitializePriorProbabilities () |
MultiLabelSTAPLEImageFilter (const Self &) ITK_DELETE_FUNCTION | |
void | operator= (const Self &) ITK_DELETE_FUNCTION |
Private Attributes | |
std::vector< ConfusionMatrixType > | m_ConfusionMatrixArray |
unsigned int | m_ElapsedNumberOfIterations |
bool | m_HasLabelForUndecidedPixels |
bool | m_HasMaximumNumberOfIterations |
bool | m_HasPriorProbabilities |
OutputPixelType | m_LabelForUndecidedPixels |
unsigned int | m_MaximumNumberOfIterations |
PriorProbabilitiesType | m_PriorProbabilities |
TWeights | m_TerminationUpdateThreshold |
vcl_size_t | m_TotalLabelCount |
std::vector< ConfusionMatrixType > | m_UpdatedConfusionMatrixArray |
Additional Inherited Members | |
Protected Types inherited from itk::ImageToImageFilter< TInputImage, TOutputImage > | |
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(OutputImageDimension), itkGetStaticConstMacro(InputImageDimension) > | InputToOutputRegionCopierType |
typedef ImageToImageFilterDetail::ImageRegionCopier< itkGetStaticConstMacro(InputImageDimension), itkGetStaticConstMacro(OutputImageDimension) > | OutputToInputRegionCopierType |
Static Protected Member Functions inherited from itk::ImageSource< TOutputImage > | |
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 Array2D<WeightsType> itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::ConfusionMatrixType |
Definition at line 159 of file itkMultiLabelSTAPLEImageFilter.h.
typedef SmartPointer< const Self > itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::ConstPointer |
Definition at line 126 of file itkMultiLabelSTAPLEImageFilter.h.
typedef ImageRegionConstIterator< TInputImage > itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::InputConstIteratorType |
Iterator types.
Definition at line 154 of file itkMultiLabelSTAPLEImageFilter.h.
typedef InputImageType::Pointer itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::InputImagePointer |
Definition at line 147 of file itkMultiLabelSTAPLEImageFilter.h.
typedef TInputImage itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::InputImageType |
Image typedef support
Definition at line 145 of file itkMultiLabelSTAPLEImageFilter.h.
typedef TInputImage::PixelType itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::InputPixelType |
Definition at line 137 of file itkMultiLabelSTAPLEImageFilter.h.
typedef OutputImageType::Pointer itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::OutputImagePointer |
Definition at line 148 of file itkMultiLabelSTAPLEImageFilter.h.
typedef Superclass::OutputImageRegionType itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::OutputImageRegionType |
Superclass typedefs.
Definition at line 151 of file itkMultiLabelSTAPLEImageFilter.h.
typedef TOutputImage itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::OutputImageType |
Definition at line 146 of file itkMultiLabelSTAPLEImageFilter.h.
typedef ImageRegionIterator< TOutputImage > itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::OutputIteratorType |
Definition at line 155 of file itkMultiLabelSTAPLEImageFilter.h.
typedef TOutputImage::PixelType itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::OutputPixelType |
Extract some information from the image types. Dimensionality of the two images is assumed to be the same.
Definition at line 132 of file itkMultiLabelSTAPLEImageFilter.h.
typedef SmartPointer< Self > itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::Pointer |
Definition at line 125 of file itkMultiLabelSTAPLEImageFilter.h.
typedef Array<WeightsType> itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::PriorProbabilitiesType |
Definition at line 160 of file itkMultiLabelSTAPLEImageFilter.h.
typedef MultiLabelSTAPLEImageFilter itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::Self |
Standard class typedefs.
Definition at line 123 of file itkMultiLabelSTAPLEImageFilter.h.
typedef ImageToImageFilter< TInputImage, TOutputImage > itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::Superclass |
Definition at line 124 of file itkMultiLabelSTAPLEImageFilter.h.
typedef TWeights itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::WeightsType |
Confusion matrix typedefs.
Definition at line 158 of file itkMultiLabelSTAPLEImageFilter.h.
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Definition at line 277 of file itkMultiLabelSTAPLEImageFilter.h.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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Definition at line 288 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::ComputeMaximumInputValue(), itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::EnlargeOutputRequestedRegion(), itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::GenerateData(), itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::GenerateInputRequestedRegion(), itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::MultiLabelSTAPLEImageFilter(), itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::operator=(), and itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::PrintSelf().
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Determine maximum value among all input images' pixels
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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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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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 from itk::ProcessObject.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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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< TOutputImage >.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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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 hierarchy. 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.
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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Get confusion matrix for the i-th input segmentation.
Definition at line 271 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_ConfusionMatrixArray.
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Get the number of elapsed iterations of the iterative E-M algorithm.
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True if LabelForUndecidedPixels has been manually set.
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True if the MaximumNumberOfIterations has been manually set.
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True if PriorProbabilities has been manually set.
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Get label value used for undecided pixels.
After updating the filter, this function returns the actual label value used for undecided pixels in the current output. Note that this value is overwritten when SetLabelForUndecidedPixels is called and the new value only becomes effective upon the next filter update.
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Set maximum number of iterations.
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Run-time type information (and related methods)
Reimplemented from itk::ImageToImageFilter< TInputImage, TOutputImage >.
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Get prior class probabilities.
After updating the filter, this function returns the actual prior class probabilities. If these were not previously set by a call to SetPriorProbabilities, then they are estimated from the input segmentations and the result is available through this function.
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Set termination threshold based on confusion matrix parameter updates.
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Method for creation through the object factory.
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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< TInputImage, TOutputImage >.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::~MultiLabelSTAPLEImageFilter().
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Set label value for undecided pixels.
Definition at line 199 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasLabelForUndecidedPixels, itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_LabelForUndecidedPixels, and itk::Object::Modified().
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Set maximum number of iterations.
Definition at line 167 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasMaximumNumberOfIterations, itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_MaximumNumberOfIterations, and itk::Object::Modified().
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Set manual estimates for the a priori class probabilities.
The size of the array must be greater than the value of the largest label. The index into the array corresponds to the label value in the segmented image for the class.
Definition at line 237 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasPriorProbabilities, itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_PriorProbabilities, and itk::Object::Modified().
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Set termination threshold based on confusion matrix parameter updates.
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Unset label value for undecided pixels and turn on automatic selection.
Definition at line 221 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasLabelForUndecidedPixels, and itk::Object::Modified().
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Unset the maximum number of iterations, and rely on the TerminationUpdateThreshold.
Definition at line 181 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasMaximumNumberOfIterations, and itk::Object::Modified().
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Unset prior class probabilities and turn on automatic estimation.
Definition at line 259 of file itkMultiLabelSTAPLEImageFilter.h.
References itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::m_HasPriorProbabilities, and itk::Object::Modified().
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Extract some information from the image types. Dimensionality of the two images is assumed to be the same.
Definition at line 142 of file itkMultiLabelSTAPLEImageFilter.h.
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Definition at line 317 of file itkMultiLabelSTAPLEImageFilter.h.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::GetConfusionMatrix().
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Definition at line 325 of file itkMultiLabelSTAPLEImageFilter.h.
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Definition at line 309 of file itkMultiLabelSTAPLEImageFilter.h.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::SetLabelForUndecidedPixels().
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Definition at line 324 of file itkMultiLabelSTAPLEImageFilter.h.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::SetMaximumNumberOfIterations().
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Definition at line 313 of file itkMultiLabelSTAPLEImageFilter.h.
Referenced by itk::MultiLabelSTAPLEImageFilter< TInputImage, TOutputImage, TWeights >::SetPriorProbabilities().
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Definition at line 327 of file itkMultiLabelSTAPLEImageFilter.h.
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Definition at line 307 of file itkMultiLabelSTAPLEImageFilter.h.
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Definition at line 318 of file itkMultiLabelSTAPLEImageFilter.h.