Medical Imaging Interaction Toolkit  2024.06.99-60d9b802
Medical Imaging Interaction Toolkit
mitk::GIFNeighbouringGreyLevelDependenceFeature Class Reference

Calculates the Neighbouring Grey Level Dependence Features. More...

#include <mitkGIFNeighbouringGreyLevelDependenceFeatures.h>

Inheritance diagram for mitk::GIFNeighbouringGreyLevelDependenceFeature:
Collaboration diagram for mitk::GIFNeighbouringGreyLevelDependenceFeature:

Public Member Functions

 mitkClassMacro (GIFNeighbouringGreyLevelDependenceFeature, AbstractGlobalImageFeature)
 
Pointer Clone () const
 
 GIFNeighbouringGreyLevelDependenceFeature ()
 
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)
 
virtual int GetAlpha () const
 
virtual void SetAlpha (int _arg)
 
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...
 
BasePropertyGetNonConstProperty (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::TimeGeometryGetTimeGeometry () const
 Return the TimeGeometry of the data as const pointer. More...
 
mitk::TimeGeometryGetTimeGeometry ()
 Return the TimeGeometry of the data as pointer. More...
 
const mitk::TimeGeometryGetUpdatedTimeGeometry ()
 Return the TimeGeometry of the data. More...
 
virtual void Expand (unsigned int timeSteps)
 Expands the TimeGeometry to a number of TimeSteps. More...
 
const mitk::BaseGeometryGetUpdatedGeometry (int t=0)
 Return the BaseGeometry of the data at time t. More...
 
mitk::BaseGeometryGetGeometry (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::BaseDataSourceGetSource () 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 ()
 
Identifiableoperator= (const Identifiable &)=delete
 
Identifiableoperator= (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< SelfPointer
 
typedef itk::SmartPointer< const SelfConstPointer
 
- 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 the Neighbouring Grey Level Dependence Features.

The Neighbouring Grey Level Dependence Features were proposed by Sun and Wee (1983) and capture the coarsness of the image texture. They are rotational invariant.

The features are calculated on a matrix \( m \). To obtain the matrix, a neighbourhood around each feature is calculated and the number of voxels within the neighbourhood that are greater than the center voxel plus \( \alpha \) is counted. This is called the number of dependence voxels. The matrix gives the number of voxels with an intensity \( x \) and \( d \) dependence neighbourhood voxels.

The image is quantified prior to the calculation of the features. This reduces the number of available intensity values. Instead of using the pure intensity value, the features are calculated using the number of the bins as intensity value \( x_i \). The parameter of the quantification of the image can be controlled using the general binning parameters as defined in AbstractGlobalImageFeature.

By default, the calculation is based on a 26 neighbourhood for 3D and a 8 neighbourhood in 2D. It is further possible to exclude directions from the calculation, e.g. calculating the feature in 2D, even if a 3D image is passed. This is controlled by determine the dimensionality of the neighbourhood using direction-related commands as described in AbstractGlobalImageFeature.

In addition to this, the size of the neighbourhood can be controlled by setting the parameter ngld::range. By default it is one. To pass more than one range, separate the ranges with a semicolon. E.g. 1;2;3 would calculate the features for the ranges 1, 2, and 3.

This feature calculator is activated by the option -neighbouring-grey-level-dependence or -ngld.

The features are calculated based on a mask. It is assumed that the mask is a unsigned short image. All voxels with a value greater 0 are treated as masked.

Several values are defined for the definition of the features. \( N_v \) is the number of masked voxels, \(N_s \) is the number of neighbourhoods, \( m_{x,\cdot} = \sum_d m{x,d} \) is the number of neighbourhoods with a given intensity value, and likewise \( m_{\cdot, d} = \sum_x m{x,d} \) is the number of neighbourhoods with a given number of dependence features:

  • Neighbouring Grey Level Dependence::Low Dependence Emphasis:

    \[ \textup{Low dependence emphasis}= \frac{1}{N_s} \sum_d { \frac{m_{\cdot, d}}{d^2} } \]

  • Neighbouring Grey Level Dependence::High Dependence Emphasis:

    \[ \textup{High dependence emphasis}= \frac{1}{N_s} \sum_d { m_{\cdot, d} d^2} \]

  • Neighbouring Grey Level Dependence::Low Grey Level Count Emphasis:

    \[ \textup{Low grey level count emphasis}= \frac{1}{N_s} \sum_x { \frac{m_{x,\cdot}}{x^2} } \]

  • Neighbouring Grey Level Dependence::High Grey Level Count Emphasis:

    \[ \textup{High grey level count emphasis}= \frac{1}{N_s} \sum_x { m_{x,\cdot} x^2} \]

  • Neighbouring Grey Level Dependence::Low Dependence Low Grey Level Emphasis:

    \[ \textup{Low Dependence Low Grey Level Emphasis}= \frac{1}{N_s} \sum_x \sum_d { \frac{m_{x,d}}{x^2 d^2} } \]

  • Neighbouring Grey Level Dependence::Low Dependence High Grey Level Emphasis:

    \[ \textup{Low dependence high grey level emphasis}= \frac{1}{N_s} \sum_x \sum_d { \frac{x^2 m_{x,d}}{d^2} } \]

  • Neighbouring Grey Level Dependence::High Dependence Low Grey Level Emphasis:

    \[ \textup{High Dependence Low Grey Level Emphasis}= \frac{1}{N_s} \sum_x \sum_d { \frac{d^2 m_{x,d}}{x^2} } \]

  • Neighbouring Grey Level Dependence::High Dependence High Grey Level Emphasis:

    \[ \textup{High dependence high grey level emphasis}= \frac{1}{N_s} \sum_x \sum_d { x^2 d^2 m_{x,d} } \]

  • Neighbouring Grey Level Dependence::Grey level nonuniformity:

    \[ \textup{Grey level nonuniformity}= \frac{1}{N_s} \sum_x m_{x,\cdot}^2 \]

  • Neighbouring Grey Level Dependence::Grey level nonuniformity normalized:

    \[ \textup{Grey level nonuniformity normalized}= \frac{1}{N_s^2} \sum_x m_{x,\cdot}^2 \]

  • Neighbouring Grey Level Dependence::Dependence Count Nonuniformity:

    \[ \textup{Dependence count nonuniformity}= \frac{1}{N_s} \sum_d m_{\cdot, d}^2 \]

  • Neighbouring Grey Level Dependence::Dependence Count Nonuniformity Normalized:

    \[ \textup{Dependence count nonuniformity normalized}= \frac{1}{N_s^2} \sum_d m_{\cdot, d}^2 \]

  • Neighbouring Grey Level Dependence::DEpendence Count Percentage THe number of realized neighbourhoods relativ to the theoretical maximum of realized neighbourhoods. This feature is always one for this implementation as partial neighbourhoods are still considered.
  • Neighbouring Grey Level Dependence::Grey Level Mean: The mean value of all grey level.

    \[ \textup{Grey Level Mean} = \mu_x = \frac{1}{N_s} \sum_x x m_{x,\cdot} \]

  • Neighbouring Grey Level Dependence::Grey Level Variance:

    \[ \textup{Grey level variance} = \frac{1}{N_s} \sum_x (x -mu_x)^2 m_{x, \cdot} \]

  • Neighbouring Grey Level Dependence::Dependence Count Mean: The mean value of all dependence counts.

    \[ \textup{Dependence count mean} = \mu_d = \frac{1}{N_s} \sum_d d m_{\cdot,d} \]

  • Neighbouring Grey Level Dependence::Dependence Count Variance:

    \[ \textup{Dependence count variance} = \frac{1}{N_s} \sum_d (d -mu_d)^2 m_{\cdot, d} \]

  • Neighbouring Grey Level Dependence::Dependence Count Entropy: This feature would be equivalent with the Grey Level Entropy, which is therefore not included. It is based on the likelihood for a given intensity- size combination \( p_{x,d} = \frac{m_{x,d}}{N_s} \). :

    \[ \textup{Dependence count entropy} = \sum_x \sum_d p_{x,d} \textup{log}_2 \left( p_{x,d} \right) \]

  • Neighbouring Grey Level Dependence::Dependence Count Energy: This feature would be equivalent with the Grey Level Energy, which is therefore not included. It is based on the likelihood for a given intensity- size combination \( p_{x,d} = \frac{m_{x,d}}{N_s} \). :

    \[ \textup{Dependence count energy} = \sum_x \sum_d p_{x,d}^2 \]

  • Neighbouring Grey Level Dependence::Expected Neighbourhood Size: The expected size of a full neighbourhood. It depends on the dimension of the area that is looked at.
  • Neighbouring Grey Level Dependence::Average Neighbourhood Size: The feature calculation allows to consider partially masked neighbourhoods. Due to that, some neighbourhoods might be smaller. This feature gives not the theoretical neighbourhood size but the average realized neighbourhood sizes.
  • Neighbouring Grey Level Dependence::Average Incomplete Neighbourhood Size: Gives the average size of all neighbourhoods that are not complete.
  • Neighbouring Grey Level Dependence::Percentage of complete Neighbourhoods: Gives the percentage of all complete neighbourhoods from all realized neighbourhoods.
  • Neighbouring Grey Level Dependence::Percentage of Dependence Neighbour Voxels: Gives the percentage of voxels in all neighbourhoods compared to the expected number of voxels.

Definition at line 116 of file mitkGIFNeighbouringGreyLevelDependenceFeatures.h.

Constructor & Destructor Documentation

◆ GIFNeighbouringGreyLevelDependenceFeature()

mitk::GIFNeighbouringGreyLevelDependenceFeature::GIFNeighbouringGreyLevelDependenceFeature ( )

Member Function Documentation

◆ AddArguments()

void mitk::GIFNeighbouringGreyLevelDependenceFeature::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::GIFNeighbouringGreyLevelDependenceFeature::CalculateFeatures ( const Image image,
const Image mask,
const Image maskNoNAN 
)
overridevirtual

◆ Clone()

Pointer mitk::GIFNeighbouringGreyLevelDependenceFeature::Clone ( ) const

◆ ConfigureSettingsByParameters()

void mitk::GIFNeighbouringGreyLevelDependenceFeature::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::GIFNeighbouringGreyLevelDependenceFeature::DoCalculateFeatures ( const Image image,
const Image mask 
)
overrideprotectedvirtual

◆ GenerateLegacyFeatureEncoding()

std::string mitk::GIFNeighbouringGreyLevelDependenceFeature::GenerateLegacyFeatureEncoding ( const FeatureID id) const
overrideprotectedvirtual

Reimplemented from mitk::AbstractGlobalImageFeature.

◆ GetAlpha()

virtual int mitk::GIFNeighbouringGreyLevelDependenceFeature::GetAlpha ( ) const
virtual

◆ GetRanges()

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

◆ mitkClassMacro()

mitk::GIFNeighbouringGreyLevelDependenceFeature::mitkClassMacro ( GIFNeighbouringGreyLevelDependenceFeature  ,
AbstractGlobalImageFeature   
)

◆ New()

static Pointer mitk::GIFNeighbouringGreyLevelDependenceFeature::New ( )
static

◆ SetAlpha()

virtual void mitk::GIFNeighbouringGreyLevelDependenceFeature::SetAlpha ( int  _arg)
virtual

◆ SetRange()

void mitk::GIFNeighbouringGreyLevelDependenceFeature::SetRange ( double  range)

◆ SetRanges()

void mitk::GIFNeighbouringGreyLevelDependenceFeature::SetRanges ( std::vector< double >  ranges)

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