Abstract base class for implementing bin-wise normalisation of data. More...

#include "stir/recon_buildblock/BinNormalisation.h"

Inheritance diagram for stir::BinNormalisation:

[legend]

Public Member Functions
void	set_defaults () override

virtual float	get_calibration_factor () const

virtual bool	is_trivial () const
	check if we would be multiplying with 1 (i.e. do nothing)

virtual bool	is_TOF_only_norm () const
	returns if the object can only handle TOF data

virtual Succeeded	set_up (const shared_ptr< const ExamInfo > &exam_info_sptr, const shared_ptr< const ProjDataInfo > &)
	initialises the object and checks if it can handle such projection data

virtual float	get_bin_efficiency (const Bin &bin) const =0
	Return the 'efficiency' factor for a single bin.

virtual void	apply (RelatedViewgrams< float > &) const
	normalise some data

virtual void	undo (RelatedViewgrams< float > &) const
	undo the normalisation of some data

void	apply (ProjData &, shared_ptr< DataSymmetriesForViewSegmentNumbers >=shared_ptr< DataSymmetriesForViewSegmentNumbers >()) const
	normalise some data

void	undo (ProjData &, shared_ptr< DataSymmetriesForViewSegmentNumbers >=shared_ptr< DataSymmetriesForViewSegmentNumbers >()) const
	undo the normalisation of some data

void	set_exam_info_sptr (const shared_ptr< const ExamInfo > _exam_info_sptr)

shared_ptr< const ExamInfo >	get_exam_info_sptr () const

Public Member Functions inherited from stir::RegisteredObjectBase
virtual std::string	get_registered_name () const =0
	Returns the name of the type of the object.

Public Member Functions inherited from stir::ParsingObject
	ParsingObject (const ParsingObject &)

ParsingObject &	operator= (const ParsingObject &)

bool	parse (std::istream &f)

bool	parse (const char *const filename)

void	ask_parameters ()

virtual std::string	parameter_info ()

Protected Member Functions
virtual void	check (const ProjDataInfo &proj_data_info) const
	check if the argument is the same as what was used for set_up()

virtual void	check (const ExamInfo &exam_info) const

virtual void	initialise_keymap ()
	Initialise all keywords.

virtual bool	post_processing ()
	This will be called at the end of the parsing.

virtual void	set_key_values ()
	This will be called before parsing or parameter_info is called.

Protected Attributes
bool	_already_set_up

shared_ptr< const ProjDataInfo >	proj_data_info_sptr

KeyParser	parser

Additional Inherited Members
Static Public Member Functions inherited from stir::RegisteredObject< BinNormalisation >
static BinNormalisation *	read_registered_object (std::istream *in, const std::string &registered_name)
	Construct a new object (of a type derived from Root, its actual type determined by the registered_name parameter) by parsing the istream.

static BinNormalisation *	ask_type_and_parameters ()
	ask the user for the type, and then calls read_registered_object(0, type)

static void	list_registered_names (std::ostream &stream)
	List all possible registered names to the stream.

Protected Types inherited from stir::RegisteredObject< BinNormalisation >
typedef BinNormalisation (	RootFactory) (std::istream *)
	The type of a root factory is a function, taking an istream* as argument, and returning a Root*.

typedef FactoryRegistry< std::string, RootFactory, interfile_less >	RegistryType
	The type of the registry.

Static Protected Member Functions inherited from stir::RegisteredObject< BinNormalisation >
static RegistryType &	registry ()
	Static function returning the registry.

Detailed Description

Abstract base class for implementing bin-wise normalisation of data.

As part of the measurement model in PET, there usually is some multiplicative correction for every bin, as in

$P^\mathrm{full}_{bv} = \mathrm{norm}_b P^\mathrm{normalised}_{bv}$

This multiplicative correction is usually split in the normalisation factors (which are scanner dependent) and the attenuation factors (which are object dependent).

The present class can be used for both of these factors.

Member Function Documentation

◆ set_defaults()

void stir::BinNormalisation::set_defaults ( )

overridevirtual

sets _already_setup to false

Reimplemented from stir::ParsingObject.

Reimplemented in stir::BinNormalisationPETFromComponents, and stir::BinNormalisationWithCalibration.

References set_defaults().

Referenced by set_defaults(), stir::BinNormalisationPETFromComponents::set_defaults(), and stir::BinNormalisationWithCalibration::set_defaults().

◆ is_trivial()

virtual bool stir::BinNormalisation::is_trivial ( ) const

inlinevirtual

check if we would be multiplying with 1 (i.e. do nothing)

This function can be used to check if the operations are guaranteed to do nothing (while potentially taking time and effort). The base-class sets this to always return false. It is up to the derived class to change this.

Reimplemented in stir::BinNormalisationFromProjData, stir::BinNormalisationPETFromComponents, and stir::TrivialBinNormalisation.

Referenced by stir::ScatterEstimation::upsample_and_fit_scatter_estimate().

◆ is_TOF_only_norm()

virtual bool stir::BinNormalisation::is_TOF_only_norm ( ) const

inlinevirtual

returns if the object can only handle TOF data

In PET, many types of normalisation classes can handle both time-of-flight (TOF) and non-TOF data. However, some classes cannot (e.g. BinNormalisationFromProjData if the "projection data" is TOF. The Poisson objective functions can adapt accordingly.

Reimplemented in stir::BinNormalisationFromProjData, and stir::ChainedBinNormalisation.

◆ set_up()

Succeeded stir::BinNormalisation::set_up	(	const shared_ptr< const ExamInfo > &	exam_info_sptr,
		const shared_ptr< const ProjDataInfo > &	proj_data_info_sptr_v )

virtual

initialises the object and checks if it can handle such projection data

Default version sets _already_set_up and stores the shared pointers.

Reimplemented in stir::BinNormalisationFromAttenuationImage, stir::BinNormalisationFromProjData, stir::BinNormalisationPETFromComponents, stir::BinNormalisationWithCalibration, stir::ChainedBinNormalisation, stir::ecat::BinNormalisationFromECAT8, stir::ecat::ecat7::BinNormalisationFromECAT7, and stir::GE::RDF_HDF5::BinNormalisationFromGEHDF5.

References set_up().

Referenced by set_up(), stir::BinNormalisationFromAttenuationImage::set_up(), stir::BinNormalisationFromProjData::set_up(), stir::BinNormalisationPETFromComponents::set_up(), stir::BinNormalisationWithCalibration::set_up(), stir::ChainedBinNormalisation::set_up(), and stir::ScatterEstimation::upsample_and_fit_scatter_estimate().

◆ get_bin_efficiency()

virtual float stir::BinNormalisation::get_bin_efficiency ( const Bin & bin ) const

pure virtual

Return the 'efficiency' factor for a single bin.

With the notation of the class documentation, this returns the factor $\mathrm{norm}_b$ .

Warning: Some derived classes might implement this very inefficiently.

Implemented in stir::BinNormalisationFromAttenuationImage, stir::BinNormalisationFromProjData, stir::BinNormalisationPETFromComponents, stir::BinNormalisationSinogramRescaling, stir::BinNormalisationWithCalibration, stir::ChainedBinNormalisation, and stir::TrivialBinNormalisation.

References apply(), check(), and undo().

Referenced by apply(), and undo().

◆ apply() [1/2]

void stir::BinNormalisation::apply ( RelatedViewgrams< float > & viewgrams ) const

virtual

normalise some data

This would be used for instance to precorrect unnormalised data. With the notation of the class documentation, this would divide by the factors $\mathrm{norm}_b$ .

Default implementation divides with the factors returned by get_bin_efficiency() (after applying a threshold to avoid division by 0).

Reimplemented in stir::BinNormalisationFromAttenuationImage, stir::BinNormalisationFromML2D, stir::BinNormalisationFromProjData, stir::BinNormalisationPETFromComponents, stir::BinNormalisationSinogramRescaling, stir::ChainedBinNormalisation, and stir::TrivialBinNormalisation.

References apply(), stir::Bin::axial_pos_num(), stir::RelatedViewgrams< elemT >::begin(), check(), stir::RelatedViewgrams< elemT >::end(), get_bin_efficiency(), stir::DataWithProjDataInfo::get_proj_data_info_sptr(), and stir::Bin::tangential_pos_num().

Referenced by apply(), apply(), and get_bin_efficiency().

◆ undo() [1/2]

void stir::BinNormalisation::undo ( RelatedViewgrams< float > & viewgrams ) const

virtual

undo the normalisation of some data

This would be used for instance to bring geometrically forward projected data to the mean of the measured data. With the notation of the class documentation, this would multiply by the factors $\mathrm{norm}_b$ .

Default implementation multiplies with the factors returned by get_bin_efficiency().

Reimplemented in stir::BinNormalisationFromAttenuationImage, stir::BinNormalisationFromML2D, stir::BinNormalisationFromProjData, stir::BinNormalisationPETFromComponents, stir::BinNormalisationSinogramRescaling, stir::ChainedBinNormalisation, and stir::TrivialBinNormalisation.

References stir::Bin::axial_pos_num(), stir::RelatedViewgrams< elemT >::begin(), check(), stir::RelatedViewgrams< elemT >::end(), get_bin_efficiency(), stir::DataWithProjDataInfo::get_proj_data_info_sptr(), stir::Bin::tangential_pos_num(), and undo().

Referenced by get_bin_efficiency(), undo(), undo(), and stir::ScatterEstimation::upsample_and_fit_scatter_estimate().

◆ apply() [2/2]

void stir::BinNormalisation::apply	(	ProjData &	proj_data,
		shared_ptr< DataSymmetriesForViewSegmentNumbers >	symmetries_sptr = shared_ptr<DataSymmetriesForViewSegmentNumbers>() ) const

normalise some data

This would be used for instance to precorrect unnormalised data. With the notation of the class documentation, this would divide by the factors $\mathrm{norm}_b$ .

This just loops over all RelatedViewgrams.

The default value for the symmetries means that TrivialDataSymmetriesForBins will be used.

References apply(), check(), stir::detail::find_basic_vs_nums_in_subset(), and stir::DataWithProjDataInfo::get_proj_data_info_sptr().

◆ undo() [2/2]

void stir::BinNormalisation::undo	(	ProjData &	proj_data,
		shared_ptr< DataSymmetriesForViewSegmentNumbers >	symmetries_sptr = shared_ptr<DataSymmetriesForViewSegmentNumbers>() ) const

undo the normalisation of some data

This would be used for instance to bring geometrically forward projected data to the mean of the measured data. With the notation of the class documentation, this would multiply by the factors $\mathrm{norm}_b$ .

This just loops over all RelatedViewgrams.

The default value for the symmetries means that TrivialDataSymmetriesForBins will be used.

References check(), stir::detail::find_basic_vs_nums_in_subset(), stir::DataWithProjDataInfo::get_max_segment_num(), stir::DataWithProjDataInfo::get_min_segment_num(), stir::DataWithProjDataInfo::get_proj_data_info_sptr(), stir::ProjData::get_related_viewgrams(), stir::ProjData::set_related_viewgrams(), and undo().

◆ check()

void stir::BinNormalisation::check ( const ProjDataInfo & proj_data_info ) const

protectedvirtual

check if the argument is the same as what was used for set_up()

calls error() if anything is wrong.

If overriding this function in a derived class, you need to call this one.

References check(), stir::error(), and stir::ProjDataInfo::parameter_info().

Referenced by apply(), apply(), stir::BinNormalisationFromAttenuationImage::apply(), stir::BinNormalisationFromProjData::apply(), stir::BinNormalisationPETFromComponents::apply(), check(), get_bin_efficiency(), undo(), undo(), stir::BinNormalisationFromAttenuationImage::undo(), stir::BinNormalisationFromProjData::undo(), and stir::BinNormalisationPETFromComponents::undo().

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

/home/kris/devel/STIRdistrib/STIR/src/include/stir/recon_buildblock/BinNormalisation.h
/home/kris/devel/STIRdistrib/STIR/src/recon_buildblock/BinNormalisation.cxx

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ set_defaults()

◆ is_trivial()

◆ is_TOF_only_norm()

◆ set_up()

◆ get_bin_efficiency()

◆ apply() [1/2]

◆ undo() [1/2]

◆ apply() [2/2]

◆ undo() [2/2]

◆ check()