mitk::GIFCooccurenceMatrix2 Class Reference

Calculates features based on the co-occurrence matrix. More...

#include <mitkGIFCooccurenceMatrix2.h>

Inheritance diagram for mitk::GIFCooccurenceMatrix2:

Collaboration diagram for mitk::GIFCooccurenceMatrix2:

Public Member Functions
	mitkClassMacro (GIFCooccurenceMatrix2, AbstractGlobalImageFeature)
Pointer	Clone () const
	GIFCooccurenceMatrix2 ()
FeatureListType	CalculateFeatures (const Image *image, const Image *mask, const Image *maskNoNAN) override
virtual std::vector< double >	GetRanges () const
void	SetRanges (std::vector< double > ranges)
void	SetRange (double range)
void	AddArguments (mitkCommandLineParser &parser) const override
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)
virtual void	SetShortName (std::string _arg)
virtual void	SetLongName (std::string _arg)
virtual void	SetFeatureClassName (std::string _arg)
virtual void	SetDirection (int _arg)
void	SetParameters (ParametersType param)
virtual std::string	GetPrefix () const
virtual std::string	GetShortName () const
virtual std::string	GetLongName () const
virtual std::string	GetFeatureClassName () const
virtual ParametersType	GetParameters () const
virtual IntensityQuantifier::Pointer	GetQuantifier ()
virtual int	GetDirection () const
virtual void	SetMinimumIntensity (double _arg)
virtual void	SetUseMinimumIntensity (bool _arg)
virtual void	SetMaximumIntensity (double _arg)
virtual void	SetUseMaximumIntensity (bool _arg)
virtual double	GetMinimumIntensity () const
virtual bool	GetUseMinimumIntensity () const
virtual double	GetMaximumIntensity () const
virtual bool	GetUseMaximumIntensity () const
virtual void	SetBinsize (double _arg)
virtual void	SetUseBinsize (bool _arg)
virtual double	GetBinsize () const
virtual bool	GetUseBinsize () const
virtual void	SetMorphMask (mitk::Image::Pointer _arg)
virtual mitk::Image::Pointer	GetMorphMask () const
virtual void	SetBins (int _arg)
virtual void	SetUseBins (bool _arg)
virtual bool	GetUseBins () const
virtual int	GetBins () const
virtual void	SetIgnoreMask (bool _arg)
virtual bool	GetIgnoreMask () const
virtual void	SetEncodeParametersInFeaturePrefix (bool _arg)
virtual bool	GetEncodeParametersInFeaturePrefix () const
virtual void	EncodeParametersInFeaturePrefixOn ()
virtual void	EncodeParametersInFeaturePrefixOff ()
std::string	GetOptionPrefix () const
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 object contains data (at least at one point in time), e.g., a set of points may be empty. More...
Public Member Functions inherited from mitk::BaseData
virtual std::vector< std::string >	GetClassHierarchy () const
virtual const char *	GetClassName () const
BaseProperty::ConstPointer	GetConstProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=true) const override
	Get property by its key. More...
std::vector< std::string >	GetPropertyKeys (const std::string &contextName="", bool includeDefaultContext=false) const override
	Query keys of existing properties. More...
std::vector< std::string >	GetPropertyContextNames () const override
	Query names of existing contexts. More...
BaseProperty *	GetNonConstProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=true) override
	Get property by its key. More...
void	SetProperty (const std::string &propertyKey, BaseProperty *property, const std::string &contextName="", bool fallBackOnDefaultContext=false) override
	Add new or change existent property. More...
void	RemoveProperty (const std::string &propertyKey, const std::string &contextName="", bool fallBackOnDefaultContext=false) override
	Removes a property. If the property does not exist, nothing will be done. 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 pointer. More...
const mitk::TimeGeometry *	GetUpdatedTimeGeometry ()
	Return the TimeGeometry of the data. More...
virtual void	Expand (unsigned int timeSteps)
	Expands the TimeGeometry to a number of TimeSteps. More...
const mitk::BaseGeometry *	GetUpdatedGeometry (int t=0)
	Return the BaseGeometry of the data at time t. More...
mitk::BaseGeometry *	GetGeometry (int t=0) const
	Return the geometry, which is a TimeGeometry, of the data as non-const pointer. More...
void	UpdateOutputInformation () override
	Update the information for this BaseData (the geometry in particular) 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, i.e., at least the Geometry and other header data has been set. More...
virtual void	Clear ()
	Calls ClearData() and InitializeEmpty();. More...
virtual bool	IsEmptyTimeStep (unsigned int t) const
	Check whether object contains data (at a specified time), e.g., a set of points may be empty. More...
void	ExecuteOperation (Operation *operation) override
	overwrite if the Data can be called by an Interactor (StateMachine). More...
virtual void	SetGeometry (BaseGeometry *aGeometry3D)
	Set the BaseGeometry of the data, which will be referenced (not copied!). Assumes the data object has only 1 time step ( is a 3D object ) and creates a new TimeGeometry which saves the given BaseGeometry. If an TimeGeometry has already been set for the object, it will be replaced after calling this function. 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 Geometry of the data. Assumes the data object has only 1 time step ( is a 3D object ) and creates a new TimeGeometry. If an TimeGeometry has already been set for the object, it will be replaced after calling this function. More...
virtual void	SetClonedTimeGeometry (const TimeGeometry *geometry)
	Set a clone of the provided TimeGeometry as TimeGeometry of the data. More...
virtual void	SetClonedGeometry (const BaseGeometry *aGeometry3D, unsigned int time)
	Set a clone of the provided geometry as 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. More...
mitk::BaseProperty::Pointer	GetProperty (const char *propertyKey) const
	Get the property (instance of BaseProperty) with key propertyKey from the PropertyList, and set it to this, respectively;. More...
void	SetProperty (const char *propertyKey, BaseProperty *property)
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 As the base data has not a data vector given by itself, the number of time steps is defined over the time sliced geometry. In sub classes, a better implementation could be over the length of the data vector. More...
itk::ModifiedTimeType	GetMTime () const override
	Get the modified time of the last change of the contents this data object or its geometry. More...
void	Graft (const DataObject *) override
Public Member Functions inherited from mitk::OperationActor
	itkTypeMacroNoParent (OperationActor) virtual ~OperationActor()
Public Member Functions inherited from mitk::Identifiable
	Identifiable ()
	Identifiable (const UIDType &uid)
	Identifiable (const Identifiable &)=delete
	Identifiable (Identifiable &&) noexcept
virtual	~Identifiable ()
Identifiable &	operator= (const Identifiable &)=delete
Identifiable &	operator= (Identifiable &&other) noexcept
virtual UIDType	GetUID () const
	Get unique ID of an object. More...
Public Member Functions inherited from mitk::IPropertyOwner
	~IPropertyOwner () override
Public Member Functions inherited from mitk::IPropertyProvider
virtual	~IPropertyProvider ()

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

Protected Member Functions
std::string	GenerateLegacyFeatureEncoding (const FeatureID &id) const override
FeatureListType	DoCalculateFeatures (const Image *image, const Image *mask) override
void	ConfigureSettingsByParameters (const ParametersType &parameters) override
Protected Member Functions inherited from mitk::AbstractGlobalImageFeature
std::vector< double >	SplitDouble (std::string str, char delimiter)
void	AddQuantifierArguments (mitkCommandLineParser &parser) const
void	ConfigureQuantifierSettingsByParameters ()
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
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::BaseData
typedef BaseData	Self
typedef itk::DataObject	Superclass
typedef itk::SmartPointer< Self >	Pointer
typedef itk::SmartPointer< const Self >	ConstPointer
Public Types inherited from mitk::Identifiable
using	UIDType = std::string
Protected Attributes inherited from mitk::BaseData
bool	m_LastRequestedRegionWasOutsideOfTheBufferedRegion
unsigned int	m_SourceOutputIndexDuplicate
bool	m_Initialized

Detailed Description

Calculates features based on the co-occurrence matrix.

The co-occurrence matrix describes the relations between voxels in a specific direction. The elements \(m_{i,k} \) of the matrix count how often a voxel with the intensity \(i \) has a neighbour in a certain direction with the intensity \( k \). The direction for each matrix is given by a directed vector \( \overrightarrow{d} \).

It is important to calculate the matrices for all possible directions in order to obtain a rotation invariant feature. For the 3D case, this means that there are 26 possible directions. Using the symmetrical properties of the co-occurrence matrix, it is then possible to calculate the features in all directions looking at 13 different directions.

The standard length of the vector is 1, e.g. looking at direct neighbours. It is possible to look at more distance neighbours. This is achieved using the parameter range which defines the distance between two neighbouring voxels in number of voxels. The default value for this is 1. It can be changes using the Method SetRange() or by passing the option cooc2::range.

There are two possible ways of combining the information obtained from the multiple directions. The first option is to calculate a common matrix for all directions and then use this matrix to calculate the describing features. The second method is to calculate a matrix for each direction, obtain the features and then report the mean and standard value of these features. Both methods are calculated by this filters and reported, distinguisehd by either an "Overall" if a single matrix is used, a "Mean" for the mean Value, or an "Std.Dev." for the standard deviation.

The connected areas are based on the binned image, the binning parameters can be set via the default parameters as described in AbstractGlobalImageFeature. The intensity used for the calculation is always equal to the bin number. It is also possible to determine the dimensionality of the neighbourhood using direction-related commands as described in AbstractGlobalImageFeature. No other options are possible beside these two options.

This feature calculator is activated by the option -cooccurence2 or -cooc2.

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

The following features are defined. We always give the notation for the overall matrix feature although those for the mean and std.dev. are basically equal. In the name, <Range> is replace by the distance of the neighbours. For the definitions of the feature, the probability of each intensity pair (i,k) \( p_{i,k} = \frac{m_{i,k}}{\sum_i \sum_k m_{i,k}} \).

In addition, the marginal sum \( p_{i,\cdot} = p_{\cdot,k=i} = \sum_k p_{i,k} \), which is identical for both axis due to the symmetrical nature of the matrix. Furthermore, the diagonal and cross diagonal features are used:

\[ p_{i-k}(l) = \sum_i \sum_k p_{i,k} \delta(l - \| i -k \| ) \enspace \enspace l = 0, \dots, N_g -1 \]

\[ p_{i+k}(l) = \sum_i \sum_k p_{i,k} \delta(l - ( i + k ) ) \enspace \enspace l = 2, \dots, 2 N_g \]

Here, \( \delta(x) \) is the dirac function, which is one for \(x=0 \) and zero otherwise.

• Co-occurenced Based Features (<Range>)::Overall Joint Maximum:

  \[ \textup{Joint Maximum}= \textup{max}(p_{i,k}) \]

• Co-occurenced Based Features (<Range>)::Overall Joint Average:

  \[ \textup{Joint Average} = \mu_{ja} = \sum_i \sum_k i p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Joint Variance:

  \[ \textup{Joint Variance} = \sum_i \sum_k (i - \mu_{ja})^2 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Joint Entropy:

  \[ \textup{Joint Entropy} = e_j = - \sum_i \sum_k p_{i,k} \textup{log}_2 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Row Maximum:

  \[ \textup{Row Maximum}= \textup{max}(p_{i,\cdot}) \]

• Co-occurenced Based Features (<Range>)::Overall Row Average:

  \[ \textup{Row Average} = \mu_{ra} = \sum_i i p_{i,\cdot} \]

• Co-occurenced Based Features (<Range>)::Overall Row Variance:

  \[ \textup{Row Variance} = \sigma^2_{i, \cdot} = \sum_i (i - \mu_{ra})^2 p_{i,\cdot} \]

• Co-occurenced Based Features (<Range>)::Overall Row Entropy:

  \[ \textup{Row Entropy} = e_r = - \sum_i p_{i,\cdot} \textup{log}_2 p_{i,\cdot} \]

• Co-occurenced Based Features (<Range>)::Overall First Row-Column Entropy:

  \[ \textup{First Row-Column Entropy} = e_1 = - \sum_i \sum_k p_{i,k} \textup{log}_2 ( p_{i,\cdot} p_{\cdot,k}) \]

• Co-occurenced Based Features (<Range>)::Overall Second Row-Column Entropy:

  \[ \textup{Second Row-Column Entropy} = e_2 = - \sum_i \sum_k p_{i,\cdot} p_{\cdot,k} \textup{log}_2 ( p_{i,\cdot} p_{\cdot,k}) \]

• Co-occurenced Based Features (<Range>)::Overall Difference Average:

  \[ \textup{Difference Average} = \mu_{da} = \sum_l l p_{i-k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Difference Variance:

  \[ \textup{Difference Variance} = \sum_l (i - \mu_{da})^2 p_{i-k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Difference Entropy:

  \[ \textup{Difference Entropy} = - \sum_l p_{i-k}(l) \textup{log}_2 p_{i-k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Sum Average:

  \[ \textup{Sum Average} = \mu_{sa} = \sum_l l p_{i+k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Sum Variance:

  \[ \textup{Sum Variance} = \sum_l (i - \mu_{sa})^2 p_{i+k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Sum Entropy:

  \[ \textup{Sum Entropy} = - \sum_l p_{i+k}(l) \textup{log}_2 p_{i+k}(l) \]

• Co-occurenced Based Features (<Range>)::Overall Angular Second Moment:

  \[ \textup{Angular Second Moment} = \sum_i \sum_k p^2_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Contrast:

  \[ \textup{Contrast} = \sum_i \sum_k (i-k)^2 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Dissimilarity:

  \[ \textup{Dissimilarity} = \sum_i \sum_k \| i-k\| p^2_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Inverse Difference:

  \[ \textup{Inverse Difference} = \sum_i \sum_k \frac{p_{i,k}}{1+\| i-k\|} \]

• Co-occurenced Based Features (<Range>)::Overall Inverse Difference Normalized:

  \[ \textup{Inverse Difference Normalized} = \sum_i \sum_k \frac{p_{i,k}}{1+\frac{\| i-k\|}{N_g}} \]

• Co-occurenced Based Features (<Range>)::Overall Inverse Difference Moment:

  \[ \textup{Inverse Difference Moment} = \sum_i \sum_k \frac{p_{i,k}}{1+ ( i-k )^2} \]

• Co-occurenced Based Features (<Range>)::Overall Inverse Difference Moment Normalized:

  \[ \textup{Inverse Difference Moment Normalized} = \sum_i \sum_k \frac{p_{i,k}}{1+\frac{( i-k ) ^2}{N_g}} \]

• Co-occurenced Based Features (<Range>)::Overall Inverse Variance:

  \[ \textup{Inverse Difference Moment Normalized} = \sum_i \sum_k \frac{p_{i,k}}{(i-k)^2} \]

• Co-occurenced Based Features (<Range>)::Overall Correlation:

  \[ \textup{Correlation} = \frac{1}{\sigma^2_{i,\cdot}} \sum_i \sum_k (i - \mu_{ra})(k - \mu_{ra}) p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Autocorrelation:

  \[ \textup{Autocorrelation} = \sum_i \sum_k i k p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Cluster Tendency:

  \[ \textup{Cluster Tendency} = \sum_i \sum_k (i + k - 2\mu_{ra})^2 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Cluster Shade:

  \[ \textup{Cluster Shade} = \sum_i \sum_k (i + k - 2\mu_{ra})^3 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall Cluster Prominence:

  \[ \textup{Cluster Prominence} = \sum_i \sum_k (i + k - 2\mu_{ra})^4 p_{i,k} \]

• Co-occurenced Based Features (<Range>)::Overall First Measure of Information Correlation:

  \[ \textup{First Measure of Information Correlation} = \frac{ e_j- e_1}{e_r} \]

• Co-occurenced Based Features (<Range>)::Overall Second Measure of Information Correlation:

  \[ \textup{Second Measure of Information Correlation} = \sqrt{1- \exp(-2 (e_2 - e_j)} \]

Definition at line 132 of file mitkGIFCooccurenceMatrix2.h.

Constructor & Destructor Documentation

GIFCooccurenceMatrix2()

mitk::GIFCooccurenceMatrix2::GIFCooccurenceMatrix2

(

)

Member Function Documentation

AddArguments()

void mitk::GIFCooccurenceMatrix2::AddArguments ( mitkCommandLineParser &  parser ) const

overridevirtual

Can be called to add all relevant argument for configuring the feature instance to the passed parser instance. Must be implemented be derived classes. For adding the quantifier arguments use AddQuantifierArguments(...) as helper function.

Implements mitk::AbstractGlobalImageFeature.

CalculateFeatures()

FeatureListType mitk::GIFCooccurenceMatrix2::CalculateFeatures ( const Image *  image, const Image *  mask, const Image *  maskNoNAN  )

overridevirtual

Implements mitk::AbstractGlobalImageFeature.

Clone()

Pointer mitk::GIFCooccurenceMatrix2::Clone

(

)

const

ConfigureSettingsByParameters()

void mitk::GIFCooccurenceMatrix2::ConfigureSettingsByParameters ( const ParametersType &  parameters )

overrideprotectedvirtual

Ensures that the instance is configured according to the information given in the passed parameters. This method will be called by SetParameters(...) after ConfigureQuantifierSettingsByParameters() was called.

Reimplemented from mitk::AbstractGlobalImageFeature.

DoCalculateFeatures()

FeatureListType mitk::GIFCooccurenceMatrix2::DoCalculateFeatures ( const Image *  image, const Image *  mask  )

overrideprotectedvirtual

Implements mitk::AbstractGlobalImageFeature.

GenerateLegacyFeatureEncoding()

std::string mitk::GIFCooccurenceMatrix2::GenerateLegacyFeatureEncoding ( const FeatureID &  id ) const

overrideprotectedvirtual

Reimplemented from mitk::AbstractGlobalImageFeature.

GetRanges()

virtual std::vector<double> mitk::GIFCooccurenceMatrix2::GetRanges ( ) const

virtual

mitkClassMacro()

mitk::GIFCooccurenceMatrix2::mitkClassMacro	(	GIFCooccurenceMatrix2	,
		AbstractGlobalImageFeature
	)

New()

static Pointer mitk::GIFCooccurenceMatrix2::New ( )

static

SetRange()

void mitk::GIFCooccurenceMatrix2::SetRange

(

double

range

)

SetRanges()

void mitk::GIFCooccurenceMatrix2::SetRanges

(

std::vector< double >

ranges

)

---

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

• mitkGIFCooccurenceMatrix2.h