cerr.dataclasses package

Submodules

cerr.dataclasses.beams module

beams module.

The beams module defines metadata for RT Plan (RTPLAN). The metadata are attributes of the Beams class.

class cerr.dataclasses.beams.Beams(PatientName: str = '', PatientID: str = '', PatientBirthDate: str = '', PatientSex: str = '', Manufacturer: str = '', ManufacturerModelName: str = '', RelationshipGroupLength: int = 0, ImagePresentationGroupLength: int = 0, PixelPaddingValue: float = 0, PlanGroupLength: int = 0, RTPlanLabel: str = '', RTPlanDate: str = '', RTPlanTime: str = '', RTPlanGeometry: str = '', TreatmentSites: ~numpy.array = <factory>, PrescriptionDescription: str = '', DoseReferenceSequence: ~numpy.array = <factory>, FractionGroupSequence: ~numpy.array = <factory>, BeamSequence: ~numpy.array = <factory>, PatientSetupSequence: ~numpy.array = <factory>, ReferencedRTGroupLength: int = 0, ReferencedStructureSetSequence: ~numpy.array = <factory>, ReferencedDoseSequence: ~numpy.array = <factory>, ReviewGroupLength: int = 0, ApprovalStatus: str = '', ReviewDate: str = '', ReviewTime: str = '', ReviewerName: str = '', SOPInstanceUID: str = '', BeamUID: str = '')[source]

Bases: object

This class defines data object for Beams in an RTPlan. The metadata is populated from DICOM. .. attribute:: PatientName

Patient’s name

type:

str

PatientID

Patient’s ID

Type:: str

PatientBirthDate

Patient’s birth date

Type:: str

PatientSex

Patient’s gender

Type:: str

Manufacturer

Equipment manufacturer

Type:: str

ManufacturerModelName

Equipment model

Type:: str

PixelPaddingValue

Pixel padding value as defined in (0028,0120) DICOM tag

Type:: float

RTPlanLabel

User-defined label for treatment plan as defined by (300A,0002) DICOM tag

Type:: str

RTPlanDate

Date treatment plan was last modified as defined by (300A,0006) DICOM tag

Type:: str

RTPlanTime

Time treatment plan was last modified as defined by (300A,0007) DICOM tag

Type:: str

RTPlanGeometry

Describes whether RT Plan is based on patient or treatment device geometry (300A,000C) tag

Type:: str

TreatmentSites

A free-text label describing the anatomical treatment site. (3010,0077) tag

Type:: np.array

PrescriptionDescription

User-defined description of treatment prescription as defined in (300A,000E)

Type:: str

FractionGroupSequence

Sequence of Fraction Groups as per (300A,0070) DICOM tag

Type:: np.array

BeamSequence

Sequence of treatment beams for current RT Plan as per (300A,00B0) DICOM tag

Type:: np.array

PatientSetupSequence

Sequence of patient setup data for current plan as per (300A,0180) DICOM tag

Type:: np.array

ReferencedStructureSetSequence

The RT Structure Set on which the RT Plan is based as per (300C,0060) DICOM tag

Type:: np.array

ReferencedDoseSequence

Sequence of Dose References.

Type:: np.array

ApprovalStatus

Approval status at the time the SOP Instance was created as per (300E,0002) DICOM tag.

Type:: str

ReviewDate

Date plan was reviewed

Type:: str

ReviewTime

Time plan was reviewed

Type:: str

ReviewerName

Reviewer name

Type:: str

SOPInstanceUID

SOP Instance UID of the Plan

Type:: str

BeamUID

pyCERR’s UID of RTPLAN

Type:: str

class cerr.dataclasses.beams.ReferenceSeq(ReferencedSOPClassUID: str = '', ReferencedSOPInstanceUID: str = '')[source]

Bases: object

This class defines referenced sequence. .. attribute:: ReferencedSOPClassUID

Referenced SOP class UID

type:

str

ReferencedSOPInstanceUID

Referenced SOP instance UID

Type:: str

class cerr.dataclasses.beams.PatientSetupSeq(PatientSetupNumber: int = 0, PatientPosition: str = '')[source]

Bases: object

This class defines patient setup sequence. .. attribute:: PatientSetupNumber

Identification number of the Patient Setup as per (300A,0182) DICOM tag

type:

int

PatientPosition

Patient position descriptor relative to the equipment as per (0018,5100) DICOM tag

Type:: str

class cerr.dataclasses.beams.BeamLimitingDevicePositionSeq(RTBeamLimitingDeviceType: str = '', LeafJawPositions: ~numpy.array = <factory>)[source]

Bases: object

This class defines data model for Sequence of beam limiting device (collimator) jaw or leaf (element) positions. .. attribute:: RTBeamLimitingDeviceType

Type of beam limiting device (collimator) as per (300A,00B8) DICOM tag

type:

str

LeafJawPositions

Positions of beam limiting device (collimator) leaf (element) or jaw pairs (in mm) in IEC BEAM LIMITING DEVICE coordinate axis appropriate to RT Beam Limiting Device Type as defined in (300A,011C) DICOM tag

Type:: np.array

class cerr.dataclasses.beams.ControlPointSequence(BeamLimitingDevicePositionSequence: ~numpy.array = <factory>, ControlPointIndex: int = 0, NominalBeamEnergy: float = 0, GantryAngle: float = 0, GantryRotationDirection: str = '', BeamLimitingDeviceAngle: float = 0, BeamLimitingDeviceRotationDirection: str = '', PatientSupportAngle: float = 0, TableTopEccentricAngle: float = 0, TableTopEccentricRotationDirection: str = '', IsocenterPosition: ~numpy.array = <factory>, SourceToSurfaceDistance: float = 0, CumulativeMetersetWeight: float = 0)[source]

Bases: object

This class defines data model for the Sequence of machine configurations describing treatment beam. .. attribute:: BeamLimitingDevicePositionSequence

Sequence of beam limiting device (collimator) jaw or leaf (element) positions as per (300A,011A) DICOM tag.

type:

np.array

ControlPointIndex

Index of current Control Point, starting at 0 for first Control Point as per (300A,0112) DICOM tag.

Type:: int

NominalBeamEnergy

Nominal Beam Energy at control point (MV/MeV) as per (300A,0114) DICOM tag

Type:: float

GantryAngle

Gantry angle of radiation source, i.e., orientation of IEC GANTRY coordinate system with respect to IEC FIXED REFERENCE coordinate system (degrees) as per (300A,011E) DICOM tag.

Type:: float

GantryRotationDirection

Direction of Gantry Rotation when viewing gantry from isocenter, for segment following Control Point as per (300A,011F) DICOM tag.

Type:: str

BeamLimitingDeviceAngle

Beam Limiting Device angle, i.e., orientation of IEC BEAM LIMITING DEVICE coordinate system with respect to IEC GANTRY coordinate system (degrees) as per (300A,0120) DICOM tag.

Type:: float

BeamLimitingDeviceRotationDirection

Direction of Beam Limiting Device Rotation when viewing beam limiting device (collimator) from radiation source, for segment following Control Point as per (300A,0121) DICOM tag

Type:: str

PatientSupportAngle

Patient Support angle, i.e., orientation of IEC PATIENT SUPPORT (turntable) coordinate system with respect to IEC FIXED REFERENCE coordinate system (degrees) as per (300A,0122) DICOM tag

Type:: float

TableTopEccentricAngle

Table Top (non-isocentric) angle, i.e., orientation of IEC TABLE TOP ECCENTRIC coordinate system with respect to IEC PATIENT SUPPORT coordinate system (degrees) as per (300A,0125) DICOM tag.

Type:: float

TableTopEccentricRotationDirection

Type:: str

IsocenterPosition

Direction of Table Top Eccentric Rotation when viewing table from above, for segment following Control Point as per (300A,0126) DICOM tag

Type:: np.array

SourceToSurfaceDistance

Source to Patient Surface (skin) distance (mm) as per (300A,0130) DICOM tag

Type:: float

CumulativeMetersetWeight

Cumulative weight to current control point as per (300A,0134) DICOM tag

Type:: float

class cerr.dataclasses.beams.RefBeamSeq(ReferencedBeamNumber: int = 0, BeamMeterset: float = 0)[source]

Bases: object

This class defies data model for the sequence of Beams in current Fraction Group contributing to dose as per (300C,0004) DICOM tag. .. attribute:: ReferencedBeamNumber

Uniquely identifies Beam specified by Beam Number as per (300C,0006) DICOM tag

type:

int

BeamMeterset

Meterset duration over which image is to be acquired, specified in Monitor units (MU) as per (3002,0032) DICOM tag

Type:: float

class cerr.dataclasses.beams.FractionGroupSeq(FractionGroupNumber: int = 0, NumberOfFractionsPlanned: int = 0, NumberOfBeams: int = 0, NumberOfBrachyApplicationSetups: int = 0, RadiationType: str = '', RefBeamSeq: ~numpy.array = <factory>)[source]

Bases: object

This class defines data model for Sequence of Fraction Groups in current Fraction Scheme as per (300A,0070) DICOM tag. .. attribute:: FractionGroupNumber

Identification number of the Fraction Group as per (300A,0071)

type:

int

NumberOfFractionsPlanned

Total number of treatments (Fractions) prescribed for current Fraction Group as per (300A,0078)

Type:: int

NumberOfBeams

Number of Beams in current Fraction Group as per (300A,0080)

Type:: int

NumberOfBrachyApplicationSetups

Number of Brachy Application Setups in current Fraction Group as per (300A,00A0)

Type:: int

RadiationType

Particle type of Beam as per (300A,00C6)

Type:: str

RefBeamSeq

Sequence of Beams in current Fraction Group contributing to dose as per (300C,0004)

Type:: np.array

class cerr.dataclasses.beams.BeamSeq(Manufacturer: str = '', BeamName: str = '', BeamType: str = '', BeamDescription: str = '', BeamNumber: int = 0, SourceAxisDistance: float = 0, BeamLimitingDevicePositionSeq: ~numpy.array = <factory>, RadiationType: str = '', TreatmentDeliveryType: str = '', NumberOfWedges: float = 0, NumberOfBoli: float = 0, NumberOfCompensators: float = 0, NumberOfBlocks: float = 0, NumberOfControlPoints: float = 0, ControlPointSequence: ~numpy.array = <factory>)[source]

Bases: object

This class defines data model for Sequence of treatment beams for current RT Plan as per (300A,00B0) DICOM tag. .. attribute:: Manufacturer

Manufacturer of the equipment to be used for beam delivery as per (0008,0070)

type:

str

BeamName

primary beam identifier (often referred to as “field identifier”) as per (300A,00C2)

Type:: str

BeamType

Motion characteristic of Beam as per (300A,00C4)

Type:: str

BeamDescription

User-defined description for Beam as per (300A,00C3)

Type:: str

BeamNumber

Identification number of the Beam as per (300A,00C0)

Type:: int

SourceAxisDistance

Radiation source to Gantry rotation axis distance of the equipment that is to be used for beam delivery (mm) as per (300A,00B4)

Type:: float

BeamLimitingDevicePositionSeq

Sequence of beam limiting device (collimator) jaw or leaf (element) sets as per (300A,00B6)

Type:: np.array

RadiationType

Particle type of Beam as per (300A,00C6)

Type:: str

TreatmentDeliveryType

Delivery Type of treatment as per (300A,00CE)

Type:: str

NumberOfWedges

Number of wedges associated with current Beam as per (300A,00D0)

Type:: float

NumberOfBoli

Number of boli associated with current Beam as per (300A,00ED)

Type:: float

NumberOfCompensators

Number of compensators associated with current Beam as per (300A,00E0)

Type:: float

NumberOfBlocks

Number of shielding blocks associated with Beam as per (300A,00F0)

Type:: float

NumberOfControlPoints

Number of control points in Beam as per (300A,0110)

Type:: float

ControlPointSequence

Sequence of machine configurations describing treatment beam as per (300A,0111)

Type:: np.array

cerr.dataclasses.beams.load_beams(file_list)[source]

This routine parses a list of DICOM files and imports metadata from RTPLAN modality into a list of pyCERR’s Beams objects

Parameters:: file_list (List[str]) – List of DICOM file paths.
Returns:: List of pyCERR’s Beam objects.
Return type:: List[cerr.dataclasses.beams.Beams]

cerr.dataclasses.deform module

structure module.

Ths deform module defines metadata for deformation (REG). The metadata are attributes of the Deform class. This module also defines routines for transforming and accessing the Deformation Vector Field metadata in CERR coordinate system.

cerr.dataclasses.deform.get_empty_list()[source]

cerr.dataclasses.deform.get_empty_np_array()[source]

class cerr.dataclasses.deform.Deform(baseScanUID: str = '', movScanUID: str = '', algorithm: str = '', algorithmParams: dict = <factory>, deformParams: dict = <factory>, deformUID: str = '', registrationTool: str = '', deformOutFileType: str = '', deformOutFilePath: str = '', dvfMatrix: numpy.ndarray = <factory>, xOffset: float = 0.0, yOffset: float = 0.0, dx: float = 0.0, dy: float = 0.0, imageOrientationPatient: <built-in function array> = <factory>, imagePositionPatientV: <built-in function array> = <factory>, zValuesV: numpy.ndarray = <factory>, Image2PhysicalTransM: numpy.ndarray = <factory>, Image2VirtualPhysicalTransM: numpy.ndarray = <factory>, cerrToDcmTransM: numpy.ndarray = <factory>)[source]

Bases: object

baseScanUID: str = ''

movScanUID: str = ''

algorithm: str = ''

algorithmParams: dict

deformParams: dict

deformUID: str = ''

registrationTool: str = ''

deformOutFileType: str = ''

deformOutFilePath: str = ''

dvfMatrix: ndarray

xOffset: float = 0.0

yOffset: float = 0.0

dx: float = 0.0

dy: float = 0.0

imageOrientationPatient: array

imagePositionPatientV: array

zValuesV: ndarray

Image2PhysicalTransM: ndarray

Image2VirtualPhysicalTransM: ndarray

cerrToDcmTransM: ndarray

convertDcmToCerrVirtualCoords()[source]

getDVFXYZVals()[source]

getDeformDict()[source]

cerr.dataclasses.deform.flipSliceOrderFlag(deform)[source]

cerr.dataclasses.dose module

dose module.

The dose module defines metadata for an RTDOSE object. The metadata are attributes of the Dose class. This module also defines routines for transforming and accessing the Dose metadata in CERR coordinate system.

class cerr.dataclasses.dose.Dose(caseNumber: int = 0, patientName: str = '', doseNumber: int = 0, doseType: str = '', doseSummationType: str = '', refBeamNumber: int = 0, refFractionGroupNumber: int = 0, numberMultiFrameImages: int = 0, doseUnits: str = '', doseScale: float = 1, fractionGroupID: str = '', numberOfTx: int = 0, orientationOfDose: str = '', imagePositionPatient: ~numpy.array = <factory>, imageOrientationPatient: ~numpy.array = <factory>, numberRepresentation: int = 0, numberOfDimensions: int = 0, sizeOfDimension1: int = 0, sizeOfDimension2: int = 0, sizeOfDimension3: int = 0, coord1OFFirstPoint: float = 0, coord2OFFirstPoint: float = 0, horizontalGridInterval: float = 0, verticalGridInterval: float = 0, doseDescription: str = '', doseEdition: str = '', unitNumber: int = 0, writer: str = '', dateWritten: str = '', planNumberOfOrigin: int = 0, planEditionOfOrigin: str = '', studyNumberOfOrigin: int = 0, studyInstanceUID: str = '', versionNumberOfProgram: str = '', xcoordOfNormaliznPoint: float = nan, ycoordOfNormaliznPoint: float = nan, zcoordOfNormaliznPoint: float = nan, doseAtNormaliznPoint: float = nan, doseError: float = nan, coord3OfFirstPoint: float = nan, depthGridInterval: float = nan, planIDOfOrigin: str = '', doseArray: ~numpy.array = <factory>, zValues: ~numpy.array = <factory>, delivered: str = '', cachedColor: str = '', cachedTime: str = '', numCachedSlices: int = 0, transferProtocol: str = '', associatedScan: int = nan, transM: ~numpy.array = <factory>, doseUID: str = '', assocScanUID: str = '', assocBeamUID: str = '', frameOfReferenceUID: str = '', refRTPlanSopInstanceUID: str = '', refStructSetSopInstanceUID: str = '', prescriptionDose: float = 0, doseOffset: float = 0, Image2PhysicalTransM: ~numpy.array = <factory>, cerrDcmSliceDirMatch: bool = False)[source]

Bases: object

This class defines data object for RTDose. The metadata is populated from DICOM.

patientName

Patient’s name

Type:: str

doseType

Type of dose as per (3004,0004). Values can be PHYSICAL, EFFECTIVE or ERROR

Type:: str

doseSummationType

Type of dose summation as per (3004,000A)

Type:: str

refBeamNumber

Referenced beam number from ReferencedRTPlanSequence

Type:: int

refFractionGroupNumber

Referenced Fraction Group number from ReferencedRTPlanSequence

Type:: int

numberMultiFrameImages

Number of image frames

Type:: int

doseUnits

Units used to describe dose. GY or RELATIVE

Type:: str

doseScale

Scaling factor that when multiplied by the dose grid data found in Pixel Data (7FE0,0010) Attribute of the Image Pixel Module, yields grid doses in the dose units as specified by Dose Units (3004,0002).

Type:: float

fractionGroupID

Fraction Group ID from Referenced RTPLAN

Type:: str

imagePositionPatient

x,y,z coordinate of the top left voxel of the dose volume.

Type:: np.array

imageOrientationPatient

Direction cosine of dose row and column with patient coordinate system.

Type:: np.array

sizeOfDimension1

Number of columns of doseArray

Type:: int

sizeOfDimension2

Number of rows of doseArray

Type:: int

sizeOfDimension3

Number of slices of doseArray

Type:: int

coord1OFFirstPoint

x-coordinate of dose in CERR virtual coordinates

Type:: float

coord2OFFirstPoint

y-coordinate of dose in CERR virtual coordinates

Type:: float

horizontalGridInterval

delta x of dose in CERR virtual coordinates

Type:: float

verticalGridInterval

delta y of dose in CERR virtual coordinates

Type:: float

writer

Equipment Manufacturer for RTDOSE delivery.

Type:: str

dateWritten

Study Date.

Type:: str

studyInstanceUID

Study Instance UID of dose.

Type:: str

xcoordOfNormaliznPoint

x-ccordinate of normalization point

Type:: float

ycoordOfNormaliznPoint

y-ccordinate of normalization point

Type:: float

zcoordOfNormaliznPoint

z-ccordinate of normalization point

Type:: float

doseAtNormaliznPoint

dose at normalization point

Type:: float

coord3OfFirstPoint

z-coordinate of dose in CERR virtual coordinates

Type:: float

doseArray

3D volume for RTODSE in doseUnits

Type:: np.array

zValues

z-coordinates of doseArray in CERR virtual coordinate system.

Type:: np.array

delivered

whether the dose was delivered.

Type:: str

transM

transformation matrix to transform dose.

Type:: np.array

doseUID

unique identifier of dose.

Type:: str

assocScanUID

associated scan’s unique identifier

Type:: str

assocBeamUID

associated RTPLAN’s unique identifier

Type:: str

frameOfReferenceUID

Frame of Reference UID

Type:: str

refRTPlanSopInstanceUID

SOP Instance UID of associated RTPLAN

Type:: str

refStructSetSopInstanceUID

SOP Instance UID of referenced RTSTRUCT

Type:: str

prescriptionDose

Prescription dose

Type:: float

doseOffset

offset value to add to doseArray

Type:: float

Image2PhysicalTransM

Transformation matrix to convert pyCERR’s dose row,col,slc to DICOM physical coordinates.

Type:: np.ndarray

cerrDcmSliceDirMatch

Flag whether pyCERR slice order matches DICOM.

Type:: bool

getNiiAffine()[source]

Routine for affine transformation of pyCERR dose object for storing in NifTi format

Returns:: 3x3 affine matrix
Return type:: np.ndarray

saveNii(niiFileName)[source]

Routine to save pyCERR Dose object to NifTi file

Parameters:: niiFileName (str) – File name including the full path to save the pyCERR dose object to NifTi file.
Returns:: 0 when NifTi file is written successfully.
Return type:: int

convertDcmToCerrVirtualCoords(planC)[source]: Routine to get scan from DICOM to pyCERR virtual coordinates. More information about virtual coordinates is on the Wiki https://github.com/cerr/pyCERR/wiki/Coordinate-system

getDoseXYZVals()[source]

Routine to obtain pyCERR dose object’s x,y,z grid coordinates. The coordinates are in pyCERR’s virtual coordinate system.

Returns:: x, y, z coordinates corresponding to the columns, rows, slices of scan voxels
Return type:: tuple

getDoseAt(xV, yV, zV)[source]

Routine to obtain dose at input x,y,z grid coordinates. The coordinates are in pyCERR’s virtual coordinate system.

Returns:: An array of dose values.
Return type:: tuple (np.array)

getAssociatedBeamNum(planC)[source]

Routine to obtain index of planC.beams that generated this RTDOSE

Parameters:: planC (cerr.plan_container.PlanC) – pyCERR’s plan container object
Returns:: index of planC.beams
Return type:: int

cerr.dataclasses.dose.loadDose(file_list)[source]

Parameters:: file_list (list) – list of files to read into pyCERR’s Dose object
Returns:: List whose elements are pyCERR Dose objects containing metadata from file_list.
Return type:: List[cerr.daatclasses.dose.Dose]

cerr.dataclasses.dose.getDoseNumFromUID(assocDoseUID, planC) → int[source]

Parameters:

assocDoseUID (str) – doseUID
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object

Returns:

index of planC.dose matching input assocDoseUID

Return type:

int

cerr.dataclasses.scan module

scan module.

This module defines pyCERR data object for images (CT, MR, PT, US). Metadata can be imported from various file formats such as DICOM, NifTi. It also provides methods to transform the Scan object to other formats such NifTi, SimpleITK and for converting images to real world units and SUV calculation.

class cerr.dataclasses.scan.Scan(scanArray: ~numpy.ndarray = <factory>, scanType: str = '', scanInfo: ~cerr.dataclasses.scan_info.ScanInfo = <factory>, uniformScanInfo: ~cerr.dataclasses.scan_info.UniformScanInfo = <factory>, scanArraySuperior: ~numpy.ndarray = <factory>, scanArrayInferior: ~numpy.ndarray = <factory>, thumbnails: ~numpy.ndarray = <factory>, transM: ~numpy.ndarray = <factory>, scanUID: str = '', assocDeformUID: str = '', assocTextureUID: str = '', assocBaseScanUID: str = '', assocMovingScanUID: str = '', Image2PhysicalTransM: ~numpy.ndarray = <factory>, Image2VirtualPhysicalTransM: ~numpy.ndarray = <factory>, cerrToDcmTransM: ~numpy.ndarray = <factory>)[source]

Bases: object

This class defines data object for volumetric images such as CT, MR, PET or derived image type.

scanArray

numpy array for the image.

Type:: np.ndarray

scanType

Type of scan. e.g. ‘CT SCAN’

Type:: str

scanInfo

scan_info object containing metadata for each scan slice

Type:: cerr.dataclasses.scan_info.ScanInfo

scanUID

unique identifier for each scan.

Type:: str

assocDeformUID

optional, UID of associated deformation object that was used to generate this scan.

Type:: str

assocTextureUID

optional, UID of associated texture object that was used to generate this scan.

Type:: str

assocBaseScanUID

optional, UID of associated base scan in the deformation that was used to generate this scan.

Type:: str

assocMovingScanUID

optional, UID of associated moving scan in the deformation that was used to generate this scan.

Type:: str

Image2PhysicalTransM

Transformation matrix to convert pyCERR row,col,slc to DICOM physical coordinates.

Type:: np.ndarray

Image2VirtualPhysicalTransM

Transformation matrix to convert pyCERR’s scan row,col,slc to pyCERR virtual coordinates.

Type:: np.ndarray

cerrToDcmTransM

Transformation matrix to convert pyCERR virtual x,y,z coordinates to DICOM physical coordinates.

Type:: np.ndarray

getScanArray()[source]

Routine to obtain image in the units defined in planC.scan[scanNum].scanInfo[slcNum].imageUnits :returns:

CTOffset is added to to scanArray such that the resulting array is in
real world units such as HU, SUV

Return type:: np.ndarray

getNiiAffine()[source]

Routine for affine transformation of pyCERR scan object for storing in NifTi format

Returns:: 3x3 affine matrix
Return type:: np.ndarray

saveNii(niiFileName)[source]

Routine to save pyCERR Scan object to NifTi file

Parameters:: niiFileName (str) – File name including the full path to save the pyCERR scan object to NifTi file.
Returns:: 0 when NifTi file is written successfully.
Return type:: int

getSitkImage()[source]

Routine to convert pyCERR Scan object to SimpleITK Image object

Returns:: SimpleITK Image
Return type:: sitk.Image

getScanXYZVals()[source]

Routine to obtain pyCERR scan object’s x,y,z grid coordinates. The coordinates are in pyCERR’s virtual coordinate system.

Returns:: x, y, z coordinates corresponding to the columns, rows, slices of scan voxels
Return type:: tuple

getScanSize()[source]

Routine to get scan dimensions.

Returns:: numRows, numCols, numSlcs of pyCERR scan object
Return type:: np.array

getScanOrientation()[source]

Routine to get orientation of sacn w.r.t. patient.

Returns:: 3-character String representing the orientation of Scans’s row, column and slice.
Return type:: str

getScanSpacing()[source]

Routine to get voxel spacing in cm.

Returns:: 3-element array containing dx, dy, dz of scan
Return type:: np.array

convertDcmToCerrVirtualCoords()[source]: Routine to get scan from DICOM to pyCERR virtual coordinates. More information about virtual coordinates is on the Wiki https://github.com/cerr/pyCERR/wiki/Coordinate-system

convertDcmToRealWorldUnits(opts={})[source]

Routine to convert pixel array from DICOM storage units to real world units.

Parameters:

opts (dict) –

Dictionary of options to convert to real world units. Currrently, only one option if supported - importMRPreciseValueFlag (yes or no) to specify whether to convert MR image from

Philips scanner to precise values.

convertToSUV(suvType='BW')[source]

Routine to convert pixel array for PET scan from DICOM storage to SUV

Parameters:: suvType (str) – optional, type of SUV. When not specified, the suvType is read from DICOM if available. When not specified and not available in DIOCM, a default value of ‘BW’ is used. Currently supported options are ‘BW’, ‘BSA’, ‘LBM’, ‘LBMJANMA’

getScanDict()[source]

Routine to get dictionary representation of scan metadata

Returns:: fields of the dictionary are attributes of the Scan object.
Return type:: dict

cerr.dataclasses.scan.flipSliceOrderFlag(scan)[source]

Routine to determine slice order for determining the origin for conversion to NifTi and SimpleITK formats.

Parameters:: scan (cerr.dataclasses.scan.Scan) – pyCERR scan object
Returns:: True when dot product of slice normal and imagePositionPatient increases with slice order
Return type:: bool

cerr.dataclasses.scan.getITKDirection(scan)[source]

Parameters:: scan (cerr.dataclasses.scan.Scan) – pyCERR scan object
Returns:: 9-element array of direction cosines of row, column and slice w.r.t. patient.
Return type:: np.ndarray

cerr.dataclasses.scan.populateScanInfoFields(s_info, ds)[source]

Parameters:

s_info (cerr.dataclasses.scan_info.ScanInfo) – pyCERR’s scanInfo object for storing metadata per slice.
ds (pydicom.dataset.Dataset) – pydicom dataset object

Returns:

scanInfo object with attributes populated from metadata from input ds.

Return type:

cerr.dataclasses.scan_info.ScanInfo

cerr.dataclasses.scan.populateRealWorldFields(s_info, perFrameSeq)[source]

Parameters:

s_info (cerr.dataclasses.scan_info.ScanInfo) – pyCERR’s scanInfo object for storing metadata per slice.
perFrameSeq (pydicom.dataset.Dataset) – pydicom dataset object or ds.PerFrameFunctionalGroupsSequence
images. (for multiFrameFlg)

Returns:

scanInfo object with attributes populated from metadata from input ds.

Return type:

cerr.dataclasses.scan_info.ScanInfo

cerr.dataclasses.scan.populateRadiopharmaFields(s_info, seq)[source]

Parameters:

s_info (cerr.dataclasses.scan_info.ScanInfo) – pyCERR’s scanInfo object for storing metadata per slice.
seq (pydicom.dataset.Dataset) – dataset containing radiopharma metadata for PET scan.

Returns:

scanInfo object with attributes populated from metadata from input ds.

Return type:

cerr.dataclasses.scan_info.ScanInfo

cerr.dataclasses.scan.parseScanInfoFields(ds, multiFrameFlg=False) -> (<class 'cerr.dataclasses.scan_info.ScanInfo'>, <property object at 0x7fceefce1cb0>, <class 'str'>)[source]

Parameters:

ds (pydicom.dataset.Dataset) – Dataset object read from DICOM file
multiFrameFlg (bool) – True when dataset is multiFrame image, otherwise False.

Returns:

scanInfo object with attributes populated from metadata from input ds.

Return type:

cerr.dataclasses.scan_info.ScanInfo

cerr.dataclasses.scan.loadSortedScanInfo(file_list)[source]

Parameters:: file_list (list) – list of files to read into pyCERR’s Scan object
Returns:: pyCERR scan object containing metadata from the file_list.
Return type:: cerr.daatclasses.scan.Scan

cerr.dataclasses.scan.getScanNumFromUID(assocScanUID, planC) → int[source]

Parameters:

assocScanUID (str) – UID of scan.
planC (cerr.plan_container.planC) – pyCERR’s plan container object.

Returns:

index within planC.scan that matches input assocScanUID.

Return type:

int

cerr.dataclasses.scan.getCERRScanArrayFromITK(itkImage, assocScanNum, planC)[source]

This routine returns a numpy array in pyCERR coordinate system (orientation) from a SimpleITK Image.

Parameters:

itkImage (SimpleITK.Image) – SimpleITK’s Image object
assocScanNum (int) – Scan index to associate orientation of itkImage in pyCERR.
planC (cerr.planC_container.planC) – pyCERR’s plan container object.

Returns:

array in CERR virtual coordinates.

Return type:

np.ndarray

cerr.dataclasses.scan_info module

scan_info module.

The scan_info module defines metadata for images (CT, PT, MR, US). The metadata are attributes of the ScanInfo class. This metadata is used to generate physical grid coordinates and for conversion of raw image to real world units.

class cerr.dataclasses.scan_info.ScanInfo(imageNumber: float = 0.0, imageType: str = '', caseNumber: int = 0, patientName: str = '', patientID: str = '', patientBirthDate: str = '', scanType: str = '', CTOffset: float = 0.0, rescaleSlope: float = 1.0, rescaleIntercept: float = 0.0, rescaleType: str = '', scaleSlope: float = nan, scaleIntercept: float = nan, realWorldValueSlope: float = nan, realWorldValueIntercept: float = nan, realWorldMeasurCodeMeaning: str = '', philipsImageUnits: str = '', philipsRescaleSlope: float = nan, philipsRescaleIntercept: float = nan, grid1Units: float = 0.0, grid2Units: float = 0.0, numberRepresentation: int = 0, bitsAllocated: int = nan, bitsStored: int = nan, pixelRepresentation: int = nan, numberOfDimensions: int = 3, sizeOfDimension1: int = 512, sizeOfDimension2: int = 512, zValue: float = 0.0, xOffset: float = 0.0, yOffset: float = 0.0, CTAir: float = 0.0, CTWater: float = 0.0, sliceThickness: float = 0.0, voxelThickness: float = 1.0, siteOfInterest: str = '', unitNumber: int = 0, seriesDescription: str = '', studyDescription: str = '', scannerType: str = '', manufacturer: str = '', scanFileName: str = '', headInOut: str = '', positionInScan: float = '', patientAttitude: str = '', bValue: float = 0.0, acquisitionDate: str = '', acquisitionTime: str = '', patientWeight: float = '', patientSize: float = '', patientBmi: float = '', patientSex: str = '', radiopharmaInfoS: float = 0.0, injectionTime: str = '', injectionDate: str = '', injectedDose: float = '', halfLife: float = '', imageUnits: str = '', suvType: str = '', petCountSource: str = '', petSeriesType: str = '', petActivityConctrScaleFactor: float = '', petNumSlices: int = '', petPrimarySourceOfCounts: str = '', petDecayCorrectionDateTime: str = '', decayCorrection: float = '', correctedImage: float = '', seriesDate: str = '', seriesTime: str = '', studyDate: str = '', studyTime: str = '', tapeOfOrigin: str = '', studyNumberOfOrigin: int = 0, scanID: str = '', scanNumber: int = 0, scanDate: str = '', CTScale: float = 0.0, distrustAbove: float = '', imageSource: str = '', transferProtocol: str = '', studyInstanceUID: str = '', seriesInstanceUID: str = '', sopInstanceUID: str = '', sopClassUID: str = '', frameOfReferenceUID: str = '', patientPosition: str = '', imageOrientationPatient: ~numpy.array = <factory>, imagePositionPatient: ~numpy.array = <factory>, windowCenter: float = '', windowWidth: float = '', temporalPositionIndex: float = '', frameAcquisitionDuration: float = '', frameReferenceDateTime: str = '')[source]

Bases: object

This class defines data object for a scan slice.

imageType

Type of scan. MR SCAN, CT SCAN, PT SCAN.

Type:: str

patientName

Patient’s name

Type:: str

patientID

Patieint’s ID

Type:: str

patientBirthDate

Patient’s date of birth

Type:: str

CTOffset

Offset to add to scanArray to get image in scanUnits (e.g. HU). This is required so as to store only (+)ve values in scanArray.

Type:: float

rescaleSlope

m in the equation Output units = m*SV + b. Slope to transform image from storage to real world units as per (0028,1053) tag.

Type:: float

rescaleIntercept

b in the equation Output units = m*SV + b. Read from (0028,1052) tag

Type:: float

rescaleType

Specifies the output units of Rescale Slope (0028,1053) and Rescale Intercept (0028,1052)

Type:: str

scaleSlope

Private tag (2005,100E) used for conversion to MR precise values

Type:: float

scaleIntercept

Private tag (2005,100D)

Type:: float

realWorldValueSlope

The Slope value in relationship between stored values (SV) and the Real World Values as per (0040,9225) tag.

Type:: float

realWorldValueIntercept

The Intercept value in relationship between stored values (SV) and the Real World values as per (0040,9224) tag.

Type:: float

realWorldMeasurCodeMeaning

Real World code value as per (0008,0100) tag

Type:: str

philipsImageUnits

Private tag containing image units as per (2005,140B)

Type:: str

philipsRescaleSlope

Private tag containing rescale slope as per (2005,140A)

Type:: float

philipsRescaleIntercept

Private tag containing rescale intercept as per (2005,1409)

Type:: float

grid1Units

delta y of the scan grid in CERR virtual coordinates

Type:: float

grid2Units

delta x of the scan grid in CERR virtual coordinates

Type:: float

bitsAllocated

Number of bits allocated for each pixel sample as per (0028,0100)

Type:: int

bitsStored

Number of bits stored for each pixel sample as per (0028,0101)

Type:: int

pixelRepresentation

Data representation of the pixel samples as per (0028,0103) 0000H - unsigned integer, 0001H - 2’s complement

Type:: int

numberOfDimensions

Number of scan dimensions

Type:: int

sizeOfDimension1

Number of rows of scanArray

Type:: int

sizeOfDimension2

Number of columns of scanArray

Type:: int

zValue

z-coordinate of the slice in CERR virtual coordinate system

Type:: float

xOffset

x-offset of the center of scanArray in CERR virtual coordinates

Type:: float

yOffset

y-offset of the center of scanArray in CERR virtual coordinates

Type:: float

sliceThickness

Nominal slice thickness as per (0018,0050).

Type:: float

voxelThickness

Physical spacing between the next and the previous slice in CERR virtual coordinates.

Type:: float

seriesDescription

Series description as per (0008,103E)

Type:: str

studyDescription

Study description as per (0008,1030)

Type:: str

scannerType

Manufacturer model name

Type:: str

manufacturer

Scanner Mmanufacturer

Type:: str

scanFileName

Location of DICOM file from which metadata was read

Type:: str

bValue

b-value of MR scan

Type:: float

acquisitionDate

Acquisition date

Type:: str

acquisitionTime

Acquisition time

Type:: str

patientWeight

Patient’s weight

Type:: float

patientSize

Patient’s size

Type:: float

patientBmi

Patient’s BMI

Type:: float

patientSex

Patient’s gender

Type:: str

injectionTime

The actual time of radiopharmaceutical administration to the patient for imaging purposes.

Type:: str

injectionDate

The actual date of radiopharmaceutical administration to the patient for imaging purposes.

Type:: str

injectedDose

The radiopharmaceutical dose administered to the patient measured in MegaBecquerels (MBq) at the Radiopharmaceutical Start DateTime (0018,1078).

Type:: float

halfLife

The radionuclide half life, in seconds, that was used in the correction of this image.

Type:: float

imageUnits

realWorldMeasurCodeMeaning when available or rescaleType.

Type:: str

suvType

The type of SUV stored in scanArray as per (0054,1006) tag.

Type:: str

petCountSource

The primary source of counts as per (0054,1002). EMISSION or TRANSMISSION

Type:: str

petSeriesType

A multi-valued indicator of the type of Series as per (0054,1000).

Type:: str

petActivityConctrScaleFactor

Used to convert the pixel data from counts to Activity Concentration (in Bq/ml) as per (7053, 1009 tag

Type:: float

petNumSlices

The number of slices in each separate volume as per (0054,0081)

Type:: int

petDecayCorrectionDateTime

The date and time to which all frames in this Image were decay corrected as per (0018,9701)

Type:: str

decayCorrection

Whether Decay (DECY) correction has been applied to image. YES or NO.

Type:: float

correctedImage

One or more values that indicate which, if any, corrections have been applied to the image as per (0028,0051)

Type:: float

seriesDate

Series date

Type:: str

seriesTime

Series yime

Type:: str

studyDate

Study date

Type:: str

studyTime

Study time

Type:: str

studyInstanceUID

Study Instance UID

Type:: str

seriesInstanceUID

Series Instance UID of image volume

Type:: str

sopInstanceUID

SOP Instance UID of image frame

Type:: str

sopClassUID

SOP Class UID of image frame

Type:: str

frameOfReferenceUID

Frame of Reference UID

Type:: str

imageOrientationPatient

Direction cosine of dose row and column with patient coordinate system.

Type:: np.array

imagePositionPatient

x,y,z coordinate of the top left voxel of the scan volume.

Type:: np.array

windowCenter

Window center used for visualization

Type:: float

windowWidth

Window width used for visualization

Type:: float

temporalPositionIndex

Temporal position in the dynamic sequence from the FrameContentSequence.

Type:: float

frameAcquisitionDuration

Duration of Frame acquisition from the FrameContentSequence.

Type:: float

frameReferenceDateTime

FrameReferenceDateTime from the FrameContentSequence

Type:: str

class cerr.dataclasses.scan_info.UniformScanInfo(sliceNumSup: int = 0, sliceNumInf: int = 0, supInfScansCreated: int = 0, minCTValue: float = 0.0, maxCTValue: float = 0.0, firstZValue: float = 0.0)[source]: Bases: object

cerr.dataclasses.structure module

structure module.

Ths structure module defines metadata for segmentation (RTSTRUCT, SEG). The metadata are attributes of the Structre class. This module also defines routines for transforming and accessing the Structure metadata in CERR coordinate system and to convert images to real world units.

class cerr.dataclasses.structure.Structure(roiNumber: int = 0, patientName: str = '', structureName: str = '', ROIInterpretedType: str = '', structureFormat: str = '', numberOfScans: int = 0, maximumNumberScans: int = 0, maximumPointsPerSegment: int = 0, maximumSegmentsPerScan: int = 0, structureEdition: str = '', writer: str = '', dateWritten: str = '', structureColor: ~typing.List = <factory>, structureDescription: str = '', roiGenerationAlgorithm: str = '', roiGenerationDescription: str = '', studyNumberOfOrigin: str = '', contour: ~typing.List = <factory>, rasterSegments: ~numpy.ndarray = <factory>, DSHPoints: ~numpy.ndarray = <factory>, orientationOfStructure: str = '', transferProtocol: str = '', visible: bool = True, strUID: str = '', assocScanUID: str = '', structSetSopInstanceUID: str = '', rasterized: bool = False, referencedFrameOfReferenceUID: str = '', referencedSeriesUID: str = '', structureFileFormat: str = '')[source]

Bases: object

This class defines data object for volumetric segmentation. The metadata can be populated from DICOM, NifTi and numpy arrays.

patientName

Patient’s name.

Type:: str

structureName

Structure’s name.

Type:: str

ROIInterpretedType

maps to DICOM tag (3006,00A4).

Type:: str

numberOfScans

Number of scan slices containing segmentation.

Type:: int

dateWritten

Date structure was created. Corresponds to DICOM tag (3006,0008) StructureSetDate.

Type:: str

structureColor

rgb triplet representing the color for this structure

Type:: List

structureDescription

Description of the structure. DICOM SeriesDescription.

Type:: str

roiGenerationAlgorithm

Permitted values are AUTOMATIC, SEMIAUTOMATIC and MANUAL

Type:: str) = Type of algorithm used to generate ROI. DICOM tag (3006,0036

roiGenerationDescription

User-defined description of technique used to generate ROI. DICOM tag (3006,0038).

Type:: str

contour

List of contours including segmentation x,y,z CERR virtual coordinates per scan slice. The ith entry in the list corresponds to the ith slice of the associated scanArray.

Type:: List

rasterSegments

Numpy array of size numSegments x 10. The columns of this array are z-value, y-value, x segment start, x segment stop, x increment, slice, row, column start, column stop, voxel thickness for that slice. Each row represents a scan segment.

Type:: np.ndarray

strUID

unique identifier for structure object

Type:: str

assocScanUID

unique identifier for the scan associated with the structure object.

Type:: str

structSetSopInstanceUID

str = “”

Type:: str

referencedFrameOfReferenceUID

UID for frame of reference

Type:: str

referencedSeriesUID

UID of structure series i.e. DICOM SeriesInstanceUID

Type:: str

structureFileFormat

File format from which structure’s metadata was populated. Permitted values are “RTSTRUCT”, “NPARRAY”, “NIFTI”.

Type:: str

saveNii(niiFileName, planC)[source]

Routine to save pyCERR Structure object to NifTi file

Parameters:

niiFileName (str) – File name including the full path to save the pyCERR scan object to NifTi file.
planC (cerr.plan_container.PlanC) – pyCERR plan container object.

Returns:

0 when NifTi file is written successfully.

Return type:

int

convertDcmToCerrVirtualCoords(planC)[source]: Routine to convert x,y,z coordinates of segmentation from DICOM to pyCERR virtual coordinates. More information about virtual coordinates is on the Wiki https://github.com/cerr/pyCERR/wiki/Coordinate-system

getStructureAssociatedScan(planC)[source]

Parameters:

planC (cerr.plan_container.PlanC) – pyCERR’s plan container object

Returns:

associated scan index for structure object based on the scan UID associated with: the structure.

Return type:

int

getSitkImage(planC)[source]

Routine to convert pyCERR Structure object to SimpleITK Image object

Returns:: SimpleITK Image with value of 1 assigned to segmented pixels
Return type:: sitk.Image

getStructDict()[source]

Routine to get dictionary representation of structure metadata

Returns:: fields of the dictionary are attributes of the Structure object.
Return type:: dict

class cerr.dataclasses.structure.Contour(referencedSopInstanceUID: str = '', referencedSopClassUID: str = '', segments: ~numpy.array = <factory>)[source]

Bases: object

This class defines data object for storing segmented contours. The metadata can be populated from DICOM, NifTi and numpy arrays.

referencedSopInstanceUID

Instance UID of associated image slice.

Type:: str

referencedSopClassUID

Class UID of associated image slice.

Type:: str

segments

array of segments.

Type:: np.array

class cerr.dataclasses.structure.Segment(points: ~numpy.ndarray = <factory>)[source]

Bases: object

This class defines data object for storing contour segments.

points

(n X 3) array containing x,y,z coordinates of the segment in pyCERR virtual coordinate system.

Type:: numpy.ndarray

cerr.dataclasses.structure.saveJson(structNumV, jsonFileName, planC)[source]

Parameters:

structNumV (List) – List of structure indices to export to JSON format.
jsonFileName (str) – JSON file name.
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object

Returns:

None

cerr.dataclasses.structure.importJson(planC, strList=None, jsonFileName=None)[source]

Parameters:

planC (cerr.plan_container.PlanC) – pyCERR’s plan container object.
strList (list of structures) – (optional) list of structure metadata imported from json. Required when jsonFileName is None.
jsonFileName – (optional) JSON file name containing structure metadata. Required when strList is None.

Returns:

pyCERR’s plan container object.

Return type:

cerr.plan_container.PlanC

cerr.dataclasses.structure.parseContours(contour_seq)[source]

This routine parses the ContourSequence metadata from DICOM and returns a list of pyCERR Contour objects.

Parameters:: contour_seq (pydicom.dataset.Dataset) – Pydicom Dataset object for ContourSequence, DICOM tag (3006,0040).
Returns:: list of pyCERR Contour objects
Return type:: List[cerr.dataclasses.structure.Contour]

cerr.dataclasses.structure.loadStructure(file_list)[source]

This routine parses a list of DICOM files and imports metadata from RTSTRUCT and SEG modalities to a list of pyCERR’s Structure objects .

Parameters:: file_list (List[str]) – List of DICOM file paths.
Returns:: List of pyCERR’s Structure objects.
Return type:: List[cerr.dataclasses.structure.Structure]

cerr.dataclasses.structure.importNii(file_list, assocScanNum, planC, labels_dict={})[source]

This routine imports segmentation from a list of nii files into planC.

Parameters:

file_list (List or str) – List of nii file paths or a string containing path for a single file.
assocScanNum (int) – index of scan in planC to associate the segmentation.
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object.
labels_dict (dict) – dictionary of index to structure name mapping. e.g. {1: ‘GTV’, 2: ‘Lung_total’}

Returns:

pyCERR’s plan container object

Return type:

cerr.plan_container.PlanC

cerr.dataclasses.structure.importStructureMask(mask3M, assocScanNum, structName, planC, structNum=None)[source]

Parameters:

mask3M (np.ndarray) – binary mask for segmentation which is of the same shape as the associated scan
assocScanNum (int) – index of scan object within planC.scan to associate the structure
structName (str) – Name of the structure
planC (cerr.plan_container.PlanC) – pyCERR’s container object
structNum (int or None) – optional, index of structure object within planC.structure to replace

Returns:

pyCERR’s container object with updated planC.structure attribute

Return type:

cerr.plan_container.PlanC

cerr.dataclasses.structure.getColorForStructNum(structNum)[source]

This routine returns the rgb color triplet to assign to a new structure object.

Parameters:: structNum (int) – index of structure object in planC.structure
Returns:: rgb triplet
Return type:: List

cerr.dataclasses.structure.copyToScan(structNum, scanNum, planC)[source]

This routine copies structure object at index structNum to scan objact at index scanNum in planC.scan.

Parameters:

structNum (int) – index of structure object in planC.structure
scanNum (int) – index of scan object in planC.scan
planC (cerr.plan_container.PlanC) – pyCERR’s planc ontainer object

Returns:

updated planC with new planC.structure element associated with scanNum

Return type:

cerr.plan_container.PlanC)

cerr.dataclasses.structure.getStructNumFromUID(assocStrUID, planC) → int[source]

This routine returns the index of the planC.structure element corresponding to the input pyCERR’s structure UID

Parameters:

assocStrUID (str) – UID of the structure object
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object

Returns:

Index of the planC.structure element corresponding to the input UID: None when there is no matching element in planC.structure corresponding to the input UID.

Return type:

int

cerr.dataclasses.structure.getStructNumFromSOPInstanceUID(assocStrUID, planC) → int[source]

This routine returns the index of the planC.structure element corresponding to the input SOP Instance UID

Parameters:

assocStrUID (str) – SOP Instance UID of the structure object
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object

Returns:

Index of the planC.structure element corresponding to the input UID: None when there is no matching element in planC.structure corresponding to the input SOP Instance UID.

Return type:

int

cerr.dataclasses.structure.calcIsocenter(strNum, planC)[source]

This routine calculates the isocenter of the input structure index in planC.structure

Parameters:

strNum (int) – Index of structure object in planC.structure
planC (cerr.plan_container.PlanC) – pyCERR’s plan container

Returns:

x,y,z coordinates in pyCERR’s virtual coordinate system for the isocenter.

Return type:

List

cerr.dataclasses.structure.getMatchingIndex(structName, strList, matchCriteria='exact')[source]

This routine returns the index of element/s from the list of structure names that match the input name.

Parameters:

structName (str) – Structure name to find a match
strList – List of structure names
matchCriteria – Criteria used to find the match ‘EXACT’ - returns indices of exact matches ‘FIRSTCHARS’ - returns indices where first characters of elements in the list match input structName

Returns:

list of matching indices from input strList

Return type:

List

cerr.dataclasses.structure.getContourPolygons(strNum, planC, rcsFlag=False)[source]

This routine returns the list of polygonal coordinates for all the segments of input structutre.

Parameters:

strNum (int) – index of structure element in planC.structure
planC (cerr.plan_container.PlanC) – pyCERR’s plan container object
rcsFlag (bool) – optional, flag to return polygonal coordinates in row,col,slc units. By default, the polygonal coordinates are returned in physical units of cm.

Returns:

list of nx3 arrays corresponding to polygonal segments, where n is the number of points in that segment,: the columns of each array are x,y,z coordinates in physical units of cm or r,c,s units.

Return type:

list

cerr.dataclasses.structure.getClosedMask(structNum, structuringElementSizeCm, planC, saveFlag=False, replaceFlag=None, procSructName=None)[source]

Function for morphological closing and hole-filling for binary masks

Parameters:

structNum – int for index of structure in planC.
structuringElementSizeCm – float for size of structuring element for closing in cm
planC – pyCERR plan container object.
saveFlag – [optional, default=False] bool flag for saving processed mask to planC.
replaceFlag – [optional, default=False] bool flag for replacing input mask with processed mask in planC.
procSructName – [optional, default=None] string for output structure name. Original structure name is used if None.

Returns:

np.ndarray(dtype=bool) for filled mask. planC: pyCERR plan container object.

Return type:

filledMask3M

cerr.dataclasses.structure.getLargestConnComps(structNum, numConnComponents, planC=None, saveFlag=None, replaceFlag=None, procSructName=None)[source]

Function to retain ‘N’ largest connected components in input binary mask

Parameters:

structNum – int for index of structure in planC (OR) np.ndarray(dtype=bool) 3D binary mask.
structuringElementSizeCm – float for desired size of structuring element for morphological closing in cm.
planC – [optional, default=None] pyCERR plan container object.
saveFlag – [optional, default=False] bool flag for importing filtered mask to planC if set to True.
replaceFlag – [optional, default=False] bool flag for replacing input mask with processed mask to planC if set to True.
procSructName – [optional, default=None] string for output structure name. Original structure name is used if empty.

Returns:

np.ndarray(dtype=bool) filtered binary mask. planC: pyCERR plan container object.

Return type:

maskOut3M

cerr.dataclasses.structure.getLabelMap(strNumV, planC, labelDict=None, dim=3)[source]

Function to create label map for user-specified structures.

Parameters:

strNumV (list) – Structure indices to be exported.
planC (plan_container.planC) – pyCERR plan_container object.
labelDict (dict) – [optional, default={}] dictionary mapping indices with structure names.
dim (int) – [optional, default=3] int indicating dimensions of output label map. When set to 3, returns 3D label map np.array(dtype=int). When set to 4, returns 4D array of binary masks (required for overlapping structures).

Returns:

np.ndarray(dtype=int) for label map.

Return type:

labelMap3M

cerr.dataclasses.structure.getMaskList(strNumV, planC, labelDict=None)[source]

Function to create list of binary masks of user-specified structures.

Parameters:

strNumV – list of structure indices to be exported.
planC – pyCERR plan_container object.
labelDict – [optional, default={}] dictionary mapping indices with structure names.

Returns:

list(dtype=bool) of binary masks.

Return type:

maskList

cerr.dataclasses package

Submodules

cerr.dataclasses.beams module

cerr.dataclasses.deform module

cerr.dataclasses.dose module

cerr.dataclasses.header module

cerr.dataclasses.scan module

cerr.dataclasses.scan_info module

cerr.dataclasses.structure module

Module contents