mitk::GIFFirstOrderHistogramStatistics Class Reference

Calculates first order features based on a histogram. More...

#include <mitkGIFFirstOrderHistogramStatistics.h>

Inheritance diagram for mitk::GIFFirstOrderHistogramStatistics:

Collaboration diagram for mitk::GIFFirstOrderHistogramStatistics:

Public Member Functions
	mitkClassMacro (GIFFirstOrderHistogramStatistics, AbstractGlobalImageFeature)
Pointer	Clone () const
	GIFFirstOrderHistogramStatistics ()
FeatureListType	CalculateFeatures (const Image *image, const Image *mask, const Image *maskNoNAN) override
	Calculate first-order histogram-based features for the given image and mask. More...
void	AddArguments (mitkCommandLineParser &parser) const override
	Add command line arguments for configuring this feature class. More...
Public Member Functions inherited from mitk::AbstractGlobalImageFeature
	mitkClassMacro (AbstractGlobalImageFeature, BaseData)
FeatureListType	CalculateFeatures (const Image *image, const Image *mask)
	Calculates the feature of this abstract interface. Does not necessarily considers the parameter settings. More...
FeatureListType	CalculateFeaturesSlicewise (const Image::Pointer &image, const Image::Pointer &mask, int sliceID)
	Calculates the given feature Slice-wise. Might not be available for an individual filter! More...
virtual void	CalculateAndAppendFeaturesSliceWise (const Image::Pointer &image, const Image::Pointer &mask, int sliceID, FeatureListType &featureList, bool checkParameterActivation=true)
	Calculates the feature of this abstract interface. Does not necessarily considers the parameter settings. More...
void	CalculateAndAppendFeatures (const Image *image, const Image *mask, const Image *maskNoNaN, FeatureListType &featureList, bool checkParameterActivation=true)
	Calculates the feature of this abstract interface. Does not necessarily considers the parameter settings. More...
virtual void	SetPrefix (std::string _arg)
	Set the prefix prepended to command line option names. More...
virtual void	SetShortName (std::string _arg)
	Set the short name used in option keys and feature names. More...
virtual void	SetLongName (std::string _arg)
	Set the long (human-readable) name of this feature class. More...
virtual void	SetFeatureClassName (std::string _arg)
	Set the feature class name used in FeatureID. More...
virtual void	SetDirection (int _arg)
	Set the direction index for directional feature computation. More...
void	SetParameters (ParametersType param)
	Set the parameter map and reconfigure the instance accordingly. More...
virtual std::string	GetPrefix () const
	Get the command line option prefix. More...
virtual std::string	GetShortName () const
	Get the short name of this feature class. More...
virtual std::string	GetLongName () const
	Get the long name of this feature class. More...
virtual std::string	GetFeatureClassName () const
	Get the feature class name. More...
virtual ParametersType	GetParameters () const
	Get the current parameter map. More...
virtual IntensityQuantifier::Pointer	GetQuantifier ()
	Get the IntensityQuantifier used for histogram-based feature computation. More...
virtual int	GetDirection () const
	Get the direction index. More...
virtual void	SetMinimumIntensity (double _arg)
	Set the minimum intensity for histogram initialization. More...
virtual void	SetUseMinimumIntensity (bool _arg)
	Set whether to use the explicit minimum intensity. More...
virtual void	SetMaximumIntensity (double _arg)
	Set the maximum intensity for histogram initialization. More...
virtual void	SetUseMaximumIntensity (bool _arg)
	Set whether to use the explicit maximum intensity. More...
virtual double	GetMinimumIntensity () const
	Get the minimum intensity for histogram initialization. More...
virtual bool	GetUseMinimumIntensity () const
	Get whether the explicit minimum intensity is used. More...
virtual double	GetMaximumIntensity () const
	Get the maximum intensity for histogram initialization. More...
virtual bool	GetUseMaximumIntensity () const
	Get whether the explicit maximum intensity is used. More...
virtual void	SetBinsize (double _arg)
	Set the histogram bin size. More...
virtual void	SetUseBinsize (bool _arg)
	Set whether to use the explicit bin size for histogram initialization. More...
virtual double	GetBinsize () const
	Get the histogram bin size. More...
virtual bool	GetUseBinsize () const
	Get whether the explicit bin size is used. More...
virtual void	SetMorphMask (mitk::Image::Pointer _arg)
	Set the morphological mask image used by some feature classes. More...
virtual mitk::Image::Pointer	GetMorphMask () const
	Get the morphological mask image. More...
virtual void	SetBins (int _arg)
	Set the number of histogram bins. More...
virtual void	SetUseBins (bool _arg)
	Set whether to use the explicit bin count for histogram initialization. More...
virtual bool	GetUseBins () const
	Get whether the explicit bin count is used. More...
virtual int	GetBins () const
	Get the number of histogram bins. More...
virtual void	SetIgnoreMask (bool _arg)
	Set whether to ignore the mask when computing histogram ranges. More...
virtual bool	GetIgnoreMask () const
	Get whether the mask is ignored for histogram range computation. More...
virtual void	SetEncodeParametersInFeaturePrefix (bool _arg)
	Set whether to encode parameter values in the feature name prefix. More...
virtual bool	GetEncodeParametersInFeaturePrefix () const
	Get whether parameter values are encoded in the feature name prefix. More...
virtual void	EncodeParametersInFeaturePrefixOn ()
	Toggle encoding of parameter values in the feature name prefix. More...
virtual void	EncodeParametersInFeaturePrefixOff ()
std::string	GetOptionPrefix () const
	Build the full option prefix string for command line parameters. More...
void	SetRequestedRegionToLargestPossibleRegion () override
	Set the RequestedRegion to the LargestPossibleRegion. More...
bool	RequestedRegionIsOutsideOfTheBufferedRegion () override
	Determine whether the RequestedRegion is outside of the BufferedRegion. More...
bool	VerifyRequestedRegion () override
	Verify that the RequestedRegion is within the LargestPossibleRegion. More...
void	SetRequestedRegion (const itk::DataObject *) override
	Set the requested region from this data object to match the requested region of the data object passed in as a parameter. More...
bool	IsEmpty () const override
	Check whether the object contains data at any time step. More...
Public Member Functions inherited from mitk::BaseData
	mitkClassMacroItkParent (BaseData, itk::DataObject)
BaseProperty::ConstPointer	GetConstProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=true) const override
	Get a const property by its key. More...
std::vector< std::string >	GetPropertyKeys (const std::string &contextName="", bool includeDefaultContext=false) const override
	Get all property keys stored in the property list. More...
std::vector< std::string >	GetPropertyContextNames () const override
	Get the names of all property contexts. More...
BaseProperty *	GetNonConstProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=true) override
	Get a non-const property by its key. More...
void	SetProperty (const std::string &propertyKey, BaseProperty *property, const std::string &contextName="", bool fallBackOnDefaultContext=false) override
	Set a property in the property list. More...
void	RemoveProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=false) override
	Remove a property from the property list. More...
const mitk::TimeGeometry *	GetTimeGeometry () const
	Return the TimeGeometry of the data as const pointer. More...
mitk::TimeGeometry *	GetTimeGeometry ()
	Return the TimeGeometry of the data as non-const pointer. More...
const mitk::TimeGeometry *	GetUpdatedTimeGeometry ()
	Return the TimeGeometry of the data after ensuring it is up-to-date. More...
virtual void	Expand (unsigned int timeSteps)
	Expand the TimeGeometry to a number of time steps. More...
const mitk::BaseGeometry *	GetUpdatedGeometry (int t=0)
	Return the BaseGeometry of the data at time step t after ensuring it is up-to-date. More...
mitk::BaseGeometry *	GetGeometry (int t=0) const
	Return the BaseGeometry of the data at time step t as a non-const pointer. More...
void	UpdateOutputInformation () override
	Update the information for this BaseData so that it can be used as an output of a BaseProcess. More...
void	CopyInformation (const itk::DataObject *data) override
	Copy information from the specified data set. More...
virtual bool	IsInitialized () const
	Check whether the data has been initialized. More...
virtual void	Clear ()
	Reset the data object by calling ClearData() and InitializeEmpty(). More...
virtual bool	IsEmptyTimeStep (unsigned int t) const
	Check whether the object contains data at the specified time step. More...
void	ExecuteOperation (Operation *operation) override
	Execute an operation on this data object. More...
virtual void	SetGeometry (BaseGeometry *aGeometry3D)
	Set the BaseGeometry of the data, which will be referenced (not copied!). More...
virtual void	SetTimeGeometry (TimeGeometry *geometry)
	Set the TimeGeometry of the data, which will be referenced (not copied!). More...
virtual void	SetClonedGeometry (const BaseGeometry *aGeometry3D)
	Set a clone of the provided geometry as the BaseGeometry of the data. More...
virtual void	SetClonedTimeGeometry (const TimeGeometry *geometry)
	Set a clone of the provided TimeGeometry as the TimeGeometry of the data. More...
virtual void	SetClonedGeometry (const BaseGeometry *aGeometry3D, unsigned int time)
	Set a clone of the provided geometry as the BaseGeometry of a given time step. More...
mitk::PropertyList::Pointer	GetPropertyList () const
	Get the data's property list. More...
void	SetPropertyList (PropertyList *propertyList)
	Set the data's property list, replacing the existing one. More...
mitk::BaseProperty::Pointer	GetProperty (const char *propertyKey) const
	Get a property by its key from the PropertyList. More...
void	SetProperty (const char *propertyKey, BaseProperty *property)
	Set a property in the PropertyList. More...
virtual void	SetOrigin (const Point3D &origin)
	Convenience method for setting the origin of the BaseGeometry instances of all time steps. More...
itk::SmartPointer< mitk::BaseDataSource >	GetSource () const
	Get the process object that generated this data object. More...
unsigned int	GetTimeSteps () const
	Get the number of time steps from the TimeGeometry. More...
itk::ModifiedTimeType	GetMTime () const override
	Get the modification time of this data object or its geometry, whichever was modified most recently. More...
void	Graft (const DataObject *) override
	Graft data and information from another data object. More...
Public Member Functions inherited from mitk::OperationActor
	itkTypeMacroNoParent (OperationActor) virtual ~OperationActor()
Public Member Functions inherited from mitk::Identifiable
	Identifiable ()
	Default constructor. Generates a new random UID. More...
	Identifiable (const UIDType &uid)
	Construct with a pre-existing UID. More...
	Identifiable (const Identifiable &)=delete
	Copy construction is deleted to prevent UID duplication. More...
	Identifiable (Identifiable &&) noexcept
	Move constructor. Transfers ownership of the UID. More...
virtual	~Identifiable ()
	Virtual destructor. More...
Identifiable &	operator= (const Identifiable &)=delete
	Copy assignment is deleted to prevent UID duplication. More...
Identifiable &	operator= (Identifiable &&other) noexcept
	Move assignment operator. Transfers ownership of the UID. More...
virtual UIDType	GetUID () const
	Get the unique identifier of this object. More...
UIDType	GetRuntimeUID () const noexcept
	Get a runtime-unique ID for this object instance. More...
Public Member Functions inherited from mitk::IPropertyOwner
	~IPropertyOwner () override
virtual bool	PropertyIsOwned (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=true) const
	Checks if a certain property exists. More...
Public Member Functions inherited from mitk::IPropertyProvider
virtual	~IPropertyProvider ()
	Virtual destructor. More...

Static Public Member Functions
static Pointer	New ()
Static Public Member Functions inherited from mitk::AbstractGlobalImageFeature
static std::string	GenerateLegacyFeatureNameWOEncoding (const FeatureID &id)

Protected Member Functions
FeatureListType	DoCalculateFeatures (const Image *image, const Image *mask) override
Protected Member Functions inherited from mitk::AbstractGlobalImageFeature
std::vector< double >	SplitDouble (std::string str, char delimiter)
void	AddQuantifierArguments (mitkCommandLineParser &parser) const
void	ConfigureQuantifierSettingsByParameters ()
virtual void	ConfigureSettingsByParameters (const ParametersType &parameters)
void	InitializeQuantifier (const Image *image, const Image *mask, unsigned int defaultBins=256)
std::string	QuantifierParameterString () const
FeatureID	CreateTemplateFeatureID (std::string settingsSuffix="", FeatureID::ParametersType additionalParams={})
virtual std::string	GenerateLegacyFeatureName (const FeatureID &id) const
virtual std::string	GenerateLegacyFeatureNamePart (const FeatureID &id) const
virtual std::string	GenerateLegacyFeatureEncoding (const FeatureID &id) const
Protected Member Functions inherited from mitk::BaseData
	BaseData ()
	BaseData (const BaseData &other)
	~BaseData () override
virtual void	InitializeTimeGeometry (unsigned int timeSteps=1)
	Initialize the TimeGeometry for a number of time steps. The TimeGeometry is initialized empty and evenly timed. In many cases it will be necessary to overwrite this in sub-classes. More...
virtual void	ClearData ()
	reset to non-initialized state, release memory More...
virtual void	InitializeEmpty ()
	Pure virtual; Must be used in subclasses to get a data object to a valid state. Should at least create one empty object and call Superclass::InitializeTimeGeometry() to ensure an existing valid geometry. More...
void	PrintSelf (std::ostream &os, itk::Indent indent) const override
Protected Member Functions inherited from mitk::Identifiable
virtual void	SetUID (const UIDType &uid)

Additional Inherited Members
Public Types inherited from mitk::AbstractGlobalImageFeature
typedef std::vector< std::pair< FeatureID, double > >	FeatureListType
using	ParametersType = FeatureID::ParametersType
Public Types inherited from mitk::Identifiable
using	UIDType = std::string
	Type alias for unique identifiers. More...
Protected Attributes inherited from mitk::BaseData
bool	m_LastRequestedRegionWasOutsideOfTheBufferedRegion
unsigned int	m_SourceOutputIndexDuplicate
bool	m_Initialized

Detailed Description

Calculates first order features based on a histogram.

This class can be used to calculate first order features based on a histogram. For each feature, two variations are given, once the value of the feature that is obtained if the mean intensity of the histogram bins is used and the histogram bin that corresponds to the feature value. See AbstractGlobalImageFeature for more information on the histogram initialization. The histogram gives a probability \(p_i\) for the intensity \(x_i\) that is linked to the bin \(i\). The histogram bins start at index 1.

This feature calculator is activated by the option "<b>-first-order-histogram</b>" or "<b>-foh</b>". Beside the options for the histogram definitions, which are given in the description of AbstractGlobalImageFeature , no additional parameters are available.

The features are calculated based on a mask. It is assumed that the mask is of the type of an unsigned short image and all voxels with an value of 1 are treated as masked.

The resulting features are:

• First Order Histogram::Mean Value: The mean intensity of all voxels, calculated by \( \mu_x = \sum p_i x_i\).
• First Order Histogram::Variance Value The variance intensity is calculated as : \( \sigma^2 = \sum p_i (x_i - \mu_x)^2\).
• First Order Histogram::Skewness Value:

  \[ skewness = \frac{\sum p_i (x_i - \mu_x)^3}{\sigma^3} \]

• First Order Histogram::Excess Kurtosis Value:

  \[ skewness = \frac{\sum p_i (x_i - \mu_x)^4}{\sigma^4} - 3 \]

• First Order Histogram::Median Value: The median intensity value based on the histogram values.
• First Order Histogram::Minimum Value: The minimum observed intensity value.
• First Order Histogram::Percentile 10 Value: The intensity that is equal or greater than 10% of all observed intensities.
• First Order Histogram::Percentile 90 Value: The intensity that is equal or greater than 90% of all observed intensities.
• First Order Histogram::Maximum Value: The maximum observerd intensity value.
• First Order Histogram::Mode Value: The most common intensity value, i.e. the value of the bin with the highest probability.
• First Order Histogram::Interquantile Range Value: The intensity difference between Percentile 75% ( \( P75\)) and Percentile 25% ( \( P25\)).
• First Order Histogram::Range Value: The difference between the observed maximum and minimum intensity.
• First Order Histogram::Mean Absolute Deviation Value:

  \[ \textup{mean absolute deviation} = \sum p_i \left \| (x_i - \mu_x) \right \| \]

• First Order Histogram::Robust Mean Value: The mean of all intensities between the 10% and 90% quantile.
• First Order Histogram::Robust Mean Absolute Deviation Value: The Mean absolute deviation for all values between the 10% and 90% quantile. It is based on the robust mean value.
• First Order Histogram::Median Absolute Deviation Value:

  \[ \textup{mean absolute deviation} = \sum p_i \left \| (x_i - \textup{median}) \right \| \]

• First Order Histogram::Coefficient of Variation Value:

  \[ \frac{\sigma_x}{\mu_x} \]

• First Order Histogram::Quantile coefficient of Dispersion Value:

  \[ \textup{Quantile coefficient of Dispersion} = \frac{P75 - P25}{P75 + P25} \]

• First Order Histogram::Entropy Value: The entropy is only based on histogram bins with a probability greater than 0.0000001:

  \[ \textup{entropy} = - \sum p_i \textup{log}_2 p_i \]

• First Order Histogram::Uniformity Value: \( \sum p_i^2 \)
• First Order Histogram::Mean Index: The mean index of all voxels, calculated by \( \mu_i = \sum p_i i\).
• First Order Histogram::Variance Index: The variance index is calculated as : \( \sigma_i^2 = \sum p_i (i - \mu_i)^2\).
• First Order Histogram::Skewness Index:

  \[ skewness = \frac{\sum p_i (i - \mu_i)^3}{\sigma_i^3} \]

• First Order Histogram::Excess Kurtosis Index:

  \[ skewness = \frac{\sum p_i (i - \mu_i)^4}{\sigma_i^4} - 3 \]

• First Order Histogram::Median Index: The median index value based on the histogram values.
• First Order Histogram::Minimum Index: The index of the minimum observed intensity value.
• First Order Histogram::Percentile 10 Index: The index oft the intensity that is equal or greater than 10% of all observed intensities.
• First Order Histogram::Percentile 90 Index: The index of the intensity that is equal or greater than 90% of all observed intensities.
• First Order Histogram::Maximum Index: The index of the maximum observerd intensity value.
• First Order Histogram::Mode Index: The index of the most common intensity value, i.e. the index of the bin with the highest probability.
• First Order Histogram::Interquantile Range Index: The index difference between Percentile 75% ( \( P75\)) and Percentile 25% ( \( P25\)).
• First Order Histogram::Range Index: The index difference between the index of the observed maximum and minimum intensity.
• First Order Histogram::Mean Absolute Deviation Index:

  \[ \textup{mean absolute deviation} = \sum p_i \left \| (i - \mu_i) \right \| \]

• First Order Histogram::Robust Mean Absolute Deviation Index: The Mean absolute deviation for all values between the 10% and 90% quantile. It is based on the robust mean value.
• First Order Histogram::Median Absolute Deviation Index:

  \[ \textup{mean absolute deviation} = \sum p_i \left \| (i - \textup{median}) \right \| \]

• First Order Histogram::Coefficient of Variation Index:

  \[ \frac{\sigma_i}{\mu_i} \]

• First Order Histogram::Quantile coefficient of Dispersion Index:

  \[ \textup{Quantile coefficient of Dispersion} = \frac{P75 - P25}{P75 + P25} \]

• First Order Histogram::Entropy Index: The entropy is only based on histogram bins with a probability greater than 0.0000001: \( \textup{entropy} = - \sum p_i \textup{log}_2 p_i \). Note that this is the same as the entropy value.
• First Order Histogram::Uniformity Index: \( \sum p_i^2 \). Note that this is the same as the uniformity value.
• First Order Histogram::Maximum Gradient: The maximum difference between the probability of three neighbouring bins. For bins at the edge of the histogram, only two bins are used for the calculation.
• First Order Histogram::Maximum Gradient Index: The index of the bin that belongs to the maximum gradient.
• First Order Histogram::Minimum Gradient: The minimum difference between the probability of three neighbouring bins. For bins at the edge of the histogram, only two bins are used for the calculation.
• First Order Histogram::Minimum Gradient Index:The index of the bin that belongs to the minimum gradient.
• First Order Histogram::Robust Mean Index: The mean index of all intensities between the 10% and 90% quantile.
• First Order Histogram::Number of Bins: The number of bins in the histogram. This is rather for control, as this parameter is likely to be determined by the configuration rather than the image.
• First Order Histogram::Bin Size: The binsize of the bins from the histogram. This is rather for control, as this parameter is likely to be determined by the configuration rather than the image.

Definition at line 88 of file mitkGIFFirstOrderHistogramStatistics.h.

Constructor & Destructor Documentation

GIFFirstOrderHistogramStatistics()

mitk::GIFFirstOrderHistogramStatistics::GIFFirstOrderHistogramStatistics

(

)

Member Function Documentation

AddArguments()

void mitk::GIFFirstOrderHistogramStatistics::AddArguments ( mitkCommandLineParser &  parser ) const

overridevirtual

Add command line arguments for configuring this feature class.

Parameters

[in,out]

parser

The command line parser to add arguments to.

Implements mitk::AbstractGlobalImageFeature.

CalculateFeatures()

FeatureListType mitk::GIFFirstOrderHistogramStatistics::CalculateFeatures ( const Image *  image, const Image *  mask, const Image *  maskNoNAN  )

overridevirtual

Calculate first-order histogram-based features for the given image and mask.

Parameters

[in]	image	The input intensity image.
[in]	mask	The binary mask defining the region of interest.
[in]	maskNoNAN	The mask with NaN voxels excluded.

Returns

A list of computed feature name-value pairs.

Implements mitk::AbstractGlobalImageFeature.

Clone()

Pointer mitk::GIFFirstOrderHistogramStatistics::Clone

(

)

const

DoCalculateFeatures()

FeatureListType mitk::GIFFirstOrderHistogramStatistics::DoCalculateFeatures ( const Image *  image, const Image *  mask  )

overrideprotectedvirtual

Implements mitk::AbstractGlobalImageFeature.

mitkClassMacro()

mitk::GIFFirstOrderHistogramStatistics::mitkClassMacro	(	GIFFirstOrderHistogramStatistics	,
		AbstractGlobalImageFeature
	)

New()

static Pointer mitk::GIFFirstOrderHistogramStatistics::New ( )

static

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

• mitkGIFFirstOrderHistogramStatistics.h