def create_dicom(x,
filename,
sp,
sz=None,
f=1,
study_uid=None,
series_uid=None,
time=datetime.datetime.now(),
storage_directory=None):
""" Create DICOM format output file from data
create_dicom(x, filename, sp) creates a new DICOM file with a
name `filename_0001.dcm' and containing data from x. The pixel scale is
given by sp which is in mm.
create_dicom(x, filename, sp, sz, f) creates a new DICOM file with a
name formed from the given filename and the frame number f, and
containing data from x. The pixel scale is given by sp, and the frame
spacing is given by sz, both of which are in mm.
create_dicom(x, filename, sp, sz, f, study_uid, series_uid, time)
uses the DICOM UIDs study_uid and series_uid, and also the
datetime, for the file. This is useful if you want to write several
frames in the same DICOM series. The UIDs can be generated
using the DICOMUID function. The time can be generated using datetime.datetime.now().
optional storage_directory parameter can set the file's storage directory path
"""
# check for inputs
if sz is None:
sz = sp
if study_uid is None:
study_uid = pydicom.uid.generate_uid()
if series_uid is None:
series_uid = pydicom.uid.generate_uid()
# get data with the appropriate limits
x = x + 1024
x = np.clip(x, 0, None)
x = np.clip(x, None, 4096)
file_meta = Dataset()
# Initial write to create DICOM file with default settings
full_filename = filename + '_' + str(f).zfill(4) + '.dcm'
full_file = full_filename
#add storage directory if needed
if storage_directory is not None:
full_filename = os.path.join(storage_directory, full_filename)
series_date = time.strftime('%Y%m%d')
series_time = time.strftime('%H%M%S')
ds = FileDataset(full_file, {}, file_meta=file_meta, preamble=b"\0" * 128)
ds.Modality = 'CT'
ds.ContentDate = str(datetime.date.today()).replace('-', '')
ds.ContentTime = str(time) #milliseconds since the epoch
ds.StudyInstanceUID = study_uid
ds.SeriesInstanceUID = series_uid
ds.SOPClassUID = 'CT Image Storage'
ds.StudyInstanceUID = study_uid
ds.SeriesInstanceUID = series_uid
ds.StudyDescription = full_file + ' Study'
ds.SeriesDescription = full_file + ' Series'
ds.StudyID = '1'
ds.SeriesNumber = 1
ds.StudyDate = series_date
ds.SeriesDate = series_date
ds.AcquisitionDate = series_date
ds.ContentDate = series_date
ds.StudyTime = series_time
ds.SeriesTime = series_time
ds.AcquisitionTime = series_time
ds.ContentTime = series_time
ds.PatientName = full_file
ds.Modality = 'CT'
ds.RescaleIntercept = '-1024'
ds.RescaleSlope = '1'
ds.RescaleType = 'HU'
ds.WindowWidth = '2000'
ds.WindowCenter = '0'
ds.ImagePositionPatient = [0.000, 0.000, float(f * sz)]
ds.ImageOrientationPatient = [1.000, 0.000, 0.000, 0.000, 1.000, 0.000]
ds.SpacingBetweenSlices = str(sz)
ds.SliceThickness = str(sz)
ds.GantryDetectorTilt = '0'
ds.SliceLocation = str(f * sz)
ds.PixelSpacing = [sp, sp]
## These are the necessary imaging components of the FileDataset object.
ds.SamplesPerPixel = 1
ds.PhotometricInterpretation = "MONOCHROME2"
ds.PixelRepresentation = 0
ds.HighBit = 15
ds.BitsStored = 16
ds.BitsAllocated = 16
ds.Columns = x.shape[1]
ds.Rows = x.shape[0]
if x.dtype != np.uint16:
x = x.astype(np.uint16)
ds.PixelData = x.tostring()
# write final file with this metadata
ds.save_as(full_filename)
def generate_dicom_from_image(image_file, **kwargs):
suffix = '.dcm'
filename_little_endian = tempfile.NamedTemporaryFile(suffix=suffix).name
image_name = image_file
img = Image.open(image_name)
# required data elements
# File meta info data elements
file_meta = Dataset()
file_meta.FileMetaInformationGroupLength = 190
file_meta.FileMetaInformationVersion = b'\x00\x01'
# secondary capture image storage
file_meta.MediaStorageSOPClassUID = '1.2.840.10008.5.1.4.1.1.7'
file_meta.MediaStorageSOPInstanceUID = kwargs['sop_instance_uid']
file_meta.TransferSyntaxUID = '1.2.840.10008.1.2.1' # explicit VR Little-endian
file_meta.ImplementationClassUID = '1.2.840.000000.1.1' # old - '1.2.840.114202.5.2'
file_meta.ImplementationVersionName = 'PF.1.0.0'
ds = FileDataset(filename_little_endian, {},
file_meta=file_meta,
preamble=b"\0" * 128)
# kwargs so far = accession, modality, procedure, tech initia, patient
# name, patient id
# Main data elements
ds.ImageType = ['ORIGINAL', 'SECONDARY']
ds.SOPClassUID = '1.2.840.10008.5.1.4.1.1.7'
ds.SOPInstanceUID = kwargs['sop_instance_uid']
ds.StudyDate = kwargs['date_of_capture']
ds.SeriesDate = kwargs['date_of_capture']
ds.AcquisitionDate = kwargs['date_of_capture']
ds.StudyTime = kwargs['time_of_capture']
ds.SeriesTime = kwargs['time_of_capture']
ds.AcquisitionTime = kwargs['time_of_capture']
ds.AccessionNumber = kwargs['accession']
ds.Modality = kwargs['modality']
ds.ConversionType = 'WSD'
ds.Manufacturer = 'PACSFORM'
ds.InstitutionName = 'LXA'
ds.ReferringPhysicianName = ''
ds.StationName = 'PACS-FORM-PC01'
ds.StudyDescription = kwargs['procedure']
ds.SeriesDescription = 'PACS FORM'
ds.InstitutionalDepartmentName = 'US'
ds.OperatorsName = kwargs['tech_initials']
ds.ManufacturerModelName = ''
ds.PatientName = kwargs['patient_name']
ds.PatientID = kwargs['patient_id']
ds.PatientBirthDate = '19850112'
ds.PatientSex = ''
ds.BodyPartExamined = ''
ds.DeviceSerialNumber = ''
ds.DateOfSecondaryCapture = kwargs['date_of_capture']
ds.TimeOfSecondaryCapture = kwargs['time_of_capture']
ds.SecondaryCaptureDeviceManufacturer = 'Shihab'
ds.SecondaryCaptureDeviceManufacturerModelName = 'PACSFORM'
ds.SecondaryCaptureDeviceSoftwareVersions = '1.0.0'
ds.SoftwareVersions = 'V1.0.0'
ds.DigitalImageFormatAcquired = ''
ds.StudyInstanceUID = kwargs['study_instance_uid']
ds.SeriesInstanceUID = kwargs['series_instance_uid']
ds.StudyID = ''
ds.SeriesNumber = "999"
ds.InstanceNumber = "1"
ds.PatientOrientation = ''
ds.SamplesPerPixel = 3 # 1 for grayscale #3 for color
ds.PhotometricInterpretation = 'RGB'
ds.Rows = img.size[1]
ds.Columns = img.size[0]
ds.BitsAllocated = 8
ds.BitsStored = 7 # NEED TO FIX THIS
ds.HighBit = 7
ds.PixelRepresentation = 0
ds.PixelData = img.tobytes()
ds.is_implicit_VR = False
ds.is_little_endian = True
return ds
def main(dir, args):
energies = [90 + i*5 for i in range(0,29)] # in MeV, they go from 90 to 230 in steps of 5 MeV
lat_sigma = [6 for energy in energies] # in mm
print(energies, lat_sigma)
parser = argparse.ArgumentParser(description='Generate an ideal CT of a water cube and a dummy RTplan with certain energy layers, defined in script. Every energy layer has a single spot at (0,0)')
parser.add_argument('--outdir', dest='outdir' , type=str, required=True )
parser.add_argument('--inDate', dest='inDate' , type=str, required=False, default='20191011')
parser.add_argument('--stDate', dest='stDate' , type=str, required=False, default='20191011')
parser.add_argument('--seDate', dest='seDate' , type=str, required=False, default='20191011')
parser.add_argument('--acDate', dest='acDate' , type=str, required=False, default='20191011')
parser.add_argument('--coDate', dest='coDate' , type=str, required=False, default='20191011')
parser.add_argument('--inTime', dest='inTime' , type=str, required=False, default='150000')
parser.add_argument('--stTime', dest='stTime' , type=str, required=False, default='150000')
parser.add_argument('--seTime', dest='seTime' , type=str, required=False, default='150000')
parser.add_argument('--acTime', dest='acTime' , type=str, required=False, default='150000')
parser.add_argument('--coTime', dest='coTime' , type=str, required=False, default='150000')
parser.add_argument('--access', dest='access' , type=str, required=False, default='0')
parser.add_argument('--manuf' , dest='manuf' , type=str, required=False, default='MGH Physics Research')
parser.add_argument('--station',dest='station' , type=str, required=False, default='Nashua')
parser.add_argument('--institution' , dest='institution', type=str, required=False, default='rbe')
parser.add_argument('--instaddr' , dest='instaddr', type=str, required=False, default='30 Fruit St, Boston MA 02114, USA')
parser.add_argument('--physician' , dest='physician', type=str, required=False, default='')
parser.add_argument('--stDesc', dest='stDesc' , type=str, required=False, default='For commissioning')
parser.add_argument('--seDesc', dest='seDesc' , type=str, required=False, default='Water cube 50x50x50cm3')
parser.add_argument('--operat', dest='operat' , type=str, required=False, default='FHG')
parser.add_argument('--manmod', dest='manmod' , type=str, required=False, default='2019')
parser.add_argument('--patname',dest='patname' , type=str, required=False, default='Cube^Water')
parser.add_argument('--patid' , dest='patid' , type=str, required=False, default='WaterCube50')
parser.add_argument('--birth' , dest='birth' , type=str, required=False, default='N/A')
parser.add_argument('--age' , dest='age' , type=str, required=False, default='N/A')
parser.add_argument('--sex' , dest='sex' , type=str, required=False, default='N/A')
parser.add_argument('--anon' , dest='anon' , type=str, required=False, default='NO')
parser.add_argument('--sw' , dest='sw' , type=str, required=False, default='pydicom1.2.2')
parser.add_argument('--lastCal',dest='lastCal' , type=str, required=False, default='')
parser.add_argument('--stuid' , dest='stuid' , type=str, required=False, default=uid.generate_uid())
parser.add_argument('--seuid' , dest='seuid' , type=str, required=False, default=uid.generate_uid())
parser.add_argument('--stid' , dest='stid' , type=str, required=False, default='1')
parser.add_argument('--sen' , dest='sen' , type=str, required=False, default='1')
parser.add_argument('--acqn' , dest='acqn' , type=str, required=False, default='1')
parser.add_argument('--forUID', dest='forUID' , type=str, required=False, default=uid.generate_uid())
parser.add_argument('--RTlabel',dest='RTlabel' , type=str, required=False, default='Test')
parser.add_argument('--RTname', dest='RTname' , type=str, required=False, default='Pristine test')
parser.add_argument('--RTdesc', dest='RTdesc' , type=str, required=False, default='Dummy energies')
parser.add_argument('--RTdate', dest='RTdate' , type=str, required=False, default='20191011')
parser.add_argument('--RTtime', dest='RTtime' , type=str, required=False, default='150000')
parser.add_argument('--RTgeom', dest='RTgeom' , type=str, required=False, default='PATIENT')
parser.add_argument('--sadX' , dest='sadX' , type=float, required=False, default=2000.0)
parser.add_argument('--sadY' , dest='sadY' , type=float, required=False, default=1800.0)
parser.add_argument('--nBlocks',dest='nBlocks' , type=int, required=False, default=0)
parser.add_argument('--isoX' , dest='isoX' , type=float, required=False, default=0.0)
parser.add_argument('--isoY' , dest='isoY' , type=float, required=False, default=0.0)
parser.add_argument('--isoZ' , dest='isoZ' , type=float, required=False, default=0.0)
parser.add_argument('--snout' , dest='snout' , type=str, required=False, default='')
parser.add_argument('--nRS' , dest='nRS' , type=int, required=False, default=0)
parser.add_argument('--rsID' , dest='rsID' , type=str, required=False, default='')
parser.add_argument('--snPos' , dest='snPos' , type=float, required=False, default=200)
parser.add_argument('--seX' , dest='seX' , type=float, required=False, default=0.0)
parser.add_argument('--seY' , dest='seY' , type=float, required=False, default=0.0)
parser.add_argument('--seZ' , dest='seZ' , type=float, required=False, default=0.0)
parser.add_argument('--ssd' , dest='ssd' , type=float, required=False, default=2000.0)
parser.add_argument('--beam' , dest='beam' , type=str , required=False, nargs='?', default='G000' )
parser.add_argument('--machine' , dest='machine' , type=str , required=False, nargs='?', default='1.1')
parser.add_argument('--dosimeter' , dest='dosimeter' , type=str , required=False, nargs='?', default='NP' )
parser.add_argument('--tuneid' , dest='tuneid' , type=str , required=False, nargs='?', default='Tune' )
parser.add_argument('--gangle' , dest='gangle' , type=int , required=False, nargs='?', default=0 )
args = parser.parse_args(args)
# Check output dir
if not os.path.exists(args.outdir):
print('Creating output folder',args.outdir)
os.mkdir(args.outdir)
os.mkdir(os.path.join(args.outdir,'ct'))
else:
print('Writing to preexisting output folder',args.outdir)
# Define geometry of water cube
rows = 512
columns = 512
slices = 512
wrows = 1 # mm
wcolumns = 1 # mm
wslices = 1 # mm
margin = 6 # pixels of air around water cube, so that water cube is 50cm * 50cm * 50cm
cube = np.full((slices, rows, columns), -1000, dtype='int16') # -1000 HU as initialization value (air)
cube[margin:-margin,margin:-margin,margin:-margin] = 0 # 0 HU cube (water)
# Generate CT image
for sl in range(slices):
# ~ break
output_file = os.path.join(args.outdir,'ct',str(sl+1)+'.dcm')
image = cube[sl]
print(output_file,image.shape)
meta = Dataset()
meta.MediaStorageSOPClassUID = '1.2.840.10008.5.1.4.1.1.2'#'CT Image Storage'
meta.MediaStorageSOPInstanceUID = uid.generate_uid()
meta.ImplementationClassUID = uid.PYDICOM_IMPLEMENTATION_UID
meta.TransferSyntaxUID = uid.ImplicitVRLittleEndian
ds = FileDataset(output_file, {}, file_meta=meta, preamble=b"\0" * 128)
ds.SpecificCharacterSet = 'ISO_IR 100'
ds.ImageType = ['DERIVED','SECONDARY','AXIAL']
ds.InstanceCreationDate = args.inDate
ds.InstanceCreationTime = args.inTime
ds.SOPClassUID = ds.file_meta.MediaStorageSOPClassUID
ds.SOPInstanceUID = ds.file_meta.MediaStorageSOPInstanceUID
ds.StudyDate = args.stDate
ds.SeriesDate = args.seDate
ds.AcquisitionDate = args.acDate
ds.ContentDate = args.coDate
ds.StudyTime = args.stTime
ds.SeriesTime = args.seTime
ds.AcquisitionTime = args.acTime
ds.ContentTime = args.coTime
ds.AccessionNumber = args.access
ds.Modality = 'CT'
ds.Manufacturer = args.manuf
ds.InstitutionName = args.institution
ds.InstitutionAddress = args.instaddr
ds.ReferringPhysicianName = args.physician
ds.StationName = args.station
ds.StudyDescription = args.stDesc
ds.SeriesDescription = args.seDesc
ds.OperatorsName = args.operat
ds.ManufacturerModelName = args.manmod
ds.PatientName = args.patname
ds.PatientID = args.patid
ds.PatientBirthDate = args.birth
ds.PatientSex = args.sex
ds.PatientAge = args.age
ds.PatientIdentityRemoved = args.anon
ds.AdditionalPatientHistory = 'Pseudo-CT'
if args.anon == "YES":
ds.DeidentificationMethod = "Manual"
ds.SliceThickness = wslices
# ~ ds.FocalSpots
# ~ ds.KVP
# ~ ds.DataCollectionDiameter
# ~ ds.ReconstructionDiameter
ds.SoftwareVersions = args.sw
# ~ ds.DistanceSourceToDetector
# ~ ds.DistanceSourceToPatient
# ~ ds.GantryDetectorTilt
# ~ ds.ExposureTime
# ~ ds.XRayTubeCurrent
# ~ ds.RotationDirection
# ~ ds.ConvolutionKerne
# ~ ds.FilterType
ds.ProtocolName = 'RESEARCH'
# ~ ds.ScanOptions = 'AXIAL MODE'
ds.DateOfLastCalibration = args.lastCal
ds.PatientPosition = 'HFS'
ds.StudyInstanceUID = args.stuid
ds.SeriesInstanceUID = args.seuid
ds.StudyID = args.stid
ds.SeriesNumber = args.sen
ds.AcquisitionNumber = args.acqn
ds.InstanceNumber = sl + 1
# Zero (origin) is at surface of water on anterior side, and centered in the other axes. Image position refers to center point of corner voxel.
ds.ImagePositionPatient = [(-columns/2+0.5)*wcolumns,(-margin+0.5)*wrows, (slices/2-0.5-sl)*wslices]
ds.ImageOrientationPatient = ['1', '0', '0', '0', '1', '0']
ds.FrameOfReferenceUID = args.forUID
ds.PositionReferenceIndicator = ''#'OM'
ds.SliceLocation = ds.ImagePositionPatient[2]
ds.SamplesPerPixel = 1
ds.PhotometricInterpretation= 'MONOCHROME2'
ds.Rows = rows
ds.Columns = columns
ds.PixelSpacing = [wcolumns, wrows]
ds.BitsAllocated = 16
ds.BitsStored = 16
ds.HighBit = 15
ds.PixelRepresentation = 1
ds.SmallestImagePixelValue = np.amin(image).tobytes()
ds.LargestImagePixelValue = np.amax(image).tobytes()
ds.WindowCenter = 0
ds.WindowWidth = 1000
ds.RescaleIntercept = 0
ds.RescaleSlope = 1
ds.RescaleType = "HU"
ds.PixelData = image.tobytes()
# ~ ds.PixelPaddingValue = -2000
ds.save_as(output_file, False)
# Generate RTplan with certain energies
meta = Dataset()
meta.MediaStorageSOPClassUID = '1.2.840.10008.5.1.4.1.1.481.8' #RT Ion Plan Storage
meta.MediaStorageSOPInstanceUID = uid.generate_uid()
meta.ImplementationClassUID = uid.PYDICOM_IMPLEMENTATION_UID
meta.TransferSyntaxUID = uid.ImplicitVRLittleEndian
output_file = os.path.join(args.outdir,'rtplan.dcm')
ds = FileDataset(output_file, {}, file_meta=meta, preamble=b"\0" * 128)
ds.SpecificCharacterSet = 'ISO_IR 100'
ds.InstanceCreationDate = args.inDate
ds.InstanceCreationTime = args.inTime
ds.SOPClassUID = ds.file_meta.MediaStorageSOPClassUID
ds.SOPInstanceUID = ds.file_meta.MediaStorageSOPInstanceUID
ds.StudyDate = args.stDate
ds.SeriesDate = args.seDate
ds.StudyTime = args.stTime
ds.SeriesTime = args.seTime
ds.AccessionNumber = ''
ds.Modality = 'RTPLAN'
ds.Manufacturer = args.manuf
ds.InstitutionName = args.institution
ds.ReferringPhysicianName = args.physician
ds.StudyDescription = args.stDesc
ds.SeriesDescription = args.seDesc
ds.OperatorsName = args.operat
ds.ManufacturerModelName = args.manmod
ds.PatientName = args.patname
ds.PatientID = args.patid
ds.PatientBirthDate = args.birth
ds.PatientSex = args.sex
ds.PatientAge = args.age
ds.PatientIdentityRemoved = args.anon
if args.anon=="YES":
ds.DeidentificationMethod = "Manual"
ds.SoftwareVersions = args.sw
ds.DateOfLastCalibration = args.lastCal
ds.StudyInstanceUID = args.stuid
ds.SeriesInstanceUID = args.seuid
ds.StudyID = args.stid
ds.SeriesNumber = args.sen
ds.InstanceNumber = args.acqn
ds.FrameOfReferenceUID = args.forUID
ds.PositionReferenceIndicator = ''
ds.RTPlanLabel = args.RTlabel
ds.RTPlanName = args.RTname
ds.RTPlanDescription = args.RTdesc
ds.RTPlanDate = args.RTdate
ds.RTPlanTime = args.RTtime
ds.RTPlanGeometry = args.RTgeom
ds.FractionGroupSequence = Sequence()
dsfx = Dataset()
dsfx.FractionGroupNumber = 1
dsfx.FractionGroupDescription = ''
dsfx.NumberOfFractionsPlanned = 1
dsfx.NumberOfBeams = 1
dsfx.NumberOfBrachyApplicationSetups = 0
dsfx.ReferencedBeamSequence = Sequence()
dsfx_b = Dataset()
dsfx_b.BeamDoseSpecificationPoint = [args.isoX,args.isoY,args.isoZ]
dsfx_b.BeamDose = 1 #dummy
dsfx_b.BeamMeterset = float(len(energies)*1e9)#1e9 protons per spot
dsfx_b.ReferencedBeamNumber = 1
dsfx.ReferencedBeamSequence.append(dsfx_b)
ds.FractionGroupSequence.append(dsfx)
ds.PatientSetupSequence = Sequence()
pss = Dataset()
pss.PatientPosition = 'HFS'
pss.PatientSetupNumber = 1
pss.PatientSetupLabel = 'Standard'
ds.PatientSetupSequence.append(pss)
ds.IonBeamSequence = Sequence()
be = Dataset()
ds.IonBeamSequence.append(be)
be.BeamName = args.beam
be.IonControlPointSequence = Sequence()
be.TreatmentMachineName = args.machine
be.InstitutionName = args.institution
be.PrimaryDosimeterUnit = args.dosimeter
be.Manufacturer = args.manuf
be.InstitutionName = args.institution
be.ManufacturerModelName = args.machine
be.InstitutionAddress = args.instaddr
be.TreatmentMachineName = args.machine
be.PrimaryDosimeterUnit = args.dosimeter
be.BeamNumber = '1'
be.BeamName = args.beam
be.BeamDescription = 'Gantry from top'
be.BeamType = 'STATIC'
be.RadiationType = 'PROTON'
be.TreatmentDeliveryType = 'TREATMENT'
be.NumberOfWedges = 0
be.NumberOfCompensators = 0
be.NumberOfBoli = 0
be.NumberOfBlocks = args.nBlocks
be.FinalCumulativeMetersetWeight = int(1e9*len(energies)) # 1e9 protons per spot (energy)
be.NumberOfControlPoints = 2*len(energies)
be.ScanMode = 'MODULATED'
be.VirtualSourceAxisDistances = [args.sadX, args.sadY]
if not args.snout == '':
be.SnoutSequence = Sequence()
sds = Dataset()
sds.AccessoryCode = args.snout
sds.SnoutID = args.snout
be.SnoutSequence.append(sds)
be.NumberOfRangeShifters = args.nRS
if args.nRS == 1:
be.RangeShifterSequence = Sequence()
rsds = Dataset()
rsds.AccessoryCode = 'Undefined Accessory Code'
rsds.RangeShifterNumber = 1
rsds.RangeShifterID = args.rsID
rsds.RangeShifterType = 'BINARY'
be.RangeShifterSequence.append(rsds)
be.NumberOfLateralSpreadingDevices = 0
be.NumberOfRangeModulators = 0
be.PatientSupportType = 'TABLE'
cweight = 0
for i,energy in enumerate(energies[::-1]):
for j in range(2):
icpoi = Dataset()
icpoi.NominalBeamEnergyUnit = 'MEV'
icpoi.ControlPointIndex = i*2 + j
icpoi.NominalBeamEnergy = str(energy)
if j == 0:
icpoi.GantryAngle = args.gangle
icpoi.GantryRotationDirection = 'NONE'
icpoi.BeamLimitingDeviceAngle = 0
icpoi.BeamLimitingDeviceRotationDirection = 'NONE'
icpoi.PatientSupportAngle = 0
icpoi.PatientSupportRotationDirection = 'NONE'
icpoi.TableTopVerticalPosition = 0
icpoi.TableTopLongitudinalPosition = 0
icpoi.TableTopLateralPosition = 0
icpoi.IsocenterPosition = [args.isoX,args.isoY,args.isoZ]
icpoi.SurfaceEntryPoint = [args.seX,args.seY,args.seZ]
icpoi.SourceToSurfaceDistance = args.ssd
icpoi.CumulativeMetersetWeight = cweight
if j == 0:
icpoi.TableTopPitchAngle = 0
icpoi.TableTopPitchRotationDirection = 'NONE'
icpoi.TableTopRollAngle = 0
icpoi.TableTopRollRotationDirection = 'NONE'
icpoi.GantryPitchAngle = 0.0
icpoi.GantryPitchRotationDirection = 'NONE'
icpoi.SnoutPosition = args.snPos
icpoi.ScanSpotTuneID = args.tuneid
icpoi.NumberOfScanSpotPositions = 1
icpoi.ScanSpotPositionMap = [0.0, 0.0]
icpoi.ScanSpotMetersetWeights = 1e9 if j == 0 else 0
cweight += icpoi.ScanSpotMetersetWeights
icpoi.ScanningSpotSize = [lat_sigma[len(energies)-i-1],lat_sigma[len(energies)-i-1]]
icpoi.NumberOfPaintings = 1
be.IonControlPointSequence.append(icpoi)
be.ReferencedPatientSetupNumber = 1
be.ReferencedToleranceTableNumber = 0
ds.ApprovalStatus = 'UNAPPROVED'
# ~ ds.ReviewDate = args.inDate
# ~ ds.ReviewTime = args.inTime
# ~ ds.ReviewerName = 'You'
ds.save_as(output_file, False)
print('Done, saved to',output_file)
def create_image_files(image, export_path):
# TODO: Fix this function, output not working
image.logger.warn(
"Creating image files: The output of these are not correct!")
patient_info = image.pinnacle.patient_info
image_header = image.image_header
image_info = image.image_info
image_set = image.image_set
currentpatientposition = image_header["patient_position"]
modality = "CT"
try:
# Also should come from header file, but not always present
modality = image_header["modality"]
except:
pass # Incase it is not present in header
img_file = os.path.join(image.path,
"ImageSet_%s.img" % (image.image["ImageSetID"]))
if os.path.isfile(img_file):
allframeslist = []
pixel_array = np.fromfile(img_file, dtype=np.short)
# will loop over every frame
for i in range(0, int(image_header["z_dim"])):
frame_array = pixel_array[i * int(image_header["x_dim"]) *
int(image_header["y_dim"]):(i + 1) *
int(image_header["x_dim"]) *
int(image_header["y_dim"])]
allframeslist.append(frame_array)
image.logger.debug("Length of frames list: " + str(len(allframeslist)))
image.logger.debug(image_info[0])
curframe = 0
for info in image_info:
sliceloc = -info["TablePosition"] * 10
instuid = info["InstanceUID"]
seriesuid = info["SeriesUID"]
classuid = info["ClassUID"]
frameuid = info["FrameUID"]
studyinstuid = info["StudyInstanceUID"]
slicenum = info["SliceNumber"]
dateofscan = image_set["scan_date"]
timeofscan = image_set["scan_time"]
file_meta = Dataset()
file_meta.MediaStorageSOPClassUID = classuid
file_meta.MediaStorageSOPInstanceUID = instuid
file_meta.TransferSyntaxUID = GTransferSyntaxUID
# this value remains static since implementation for creating
# file is the same
file_meta.ImplementationClassUID = GImplementationClassUID
image_file_name = modality + "." + instuid + ".dcm"
ds = FileDataset(image_file_name, {},
file_meta=file_meta,
preamble=b"\x00" * 128)
ds.SpecificCharacterSet = "ISO_IR 100"
ds.ImageType = ["ORIGINAL", "PRIMARY", "AXIAL"]
ds.AccessionNumber = ""
ds.SOPClassUID = classuid
ds.SOPInstanceUID = instuid
ds.StudyDate = dateofscan
ds.SeriesDate = dateofscan
ds.AcquisitionDate = dateofscan
ds.ContentDate = dateofscan
ds.AcquisitionTime = timeofscan
ds.Modality = modality
# This should come from Manufacturer in header, but for some
# patients it isn't set??
ds.Manufacturer = ""
ds.StationName = modality
ds.PatientsName = patient_info["FullName"]
ds.PatientID = patient_info["MedicalRecordNumber"]
ds.PatientsBirthDate = patient_info["DOB"]
ds.BitsAllocated = 16
ds.BitsStored = 16
ds.HighBit = 15
ds.PixelRepresentation = 1
ds.RescaleIntercept = -1024
ds.RescaleSlope = 1.0
# ds.kvp = ?? This should be peak kilovoltage output of x ray
# generator used
ds.PatientPosition = currentpatientposition
# this is probably x_pixdim * xdim = y_pixdim * ydim
ds.DataCollectionDiameter = (float(image_header["x_pixdim"]) * 10 *
float(image_header["x_dim"]))
# ds.SpatialResolution = 0.35 # ???????
# # ds.DistanceSourceToDetector = #???
# # ds.DistanceSourceToPatient = #????
# ds.GantryDetectorTilt = 0.0 # ??
# ds.TableHeight = -158.0 # ??
# ds.RotationDirection = "CW" # ???
# ds.ExposureTime = 1000 # ??
# ds.XRayTubeCurrent = 398 # ??
# ds.GeneratorPower = 48 # ??
# ds.FocalSpots = 1.2 # ??
# ds.ConvolutionKernel = "STND" # ????
ds.SliceThickness = float(image_header["z_pixdim"]) * 10
ds.NumberOfSlices = int(image_header["z_dim"])
# ds.StudyInstanceUID = studyinstuid
# ds.SeriesInstanceUID = seriesuid
ds.FrameOfReferenceUID = info["FrameUID"]
ds.StudyInstanceUID = info["StudyInstanceUID"]
ds.SeriesInstanceUID = info["SeriesUID"]
# problem, some of these are repeated in image file so not sure
# what to do with that
ds.InstanceNumber = slicenum
ds.ImagePositionPatient = [
-float(image_header["x_pixdim"]) * 10 *
float(image_header["x_dim"]) / 2,
-float(image_header["y_pixdim"]) * 10 *
float(image_header["y_dim"]) / 2,
sliceloc,
]
if "HFS" in currentpatientposition or "FFS" in currentpatientposition:
ds.ImageOrientationPatient = [1.0, 0.0, 0.0, 0.0, 1.0, -0.0]
elif "HFP" in currentpatientposition or "FFP" in currentpatientposition:
ds.ImageOrientationPatient = [-1.0, 0.0, 0.0, 0.0, -1.0, -0.0]
ds.PositionReferenceIndicator = "LM" # ???
ds.SliceLocation = sliceloc
ds.SamplesPerPixel = 1
ds.PhotometricInterpretation = "MONOCHROME2"
ds.Rows = int(image_header["x_dim"])
ds.Columns = int(image_header["y_dim"])
ds.PixelSpacing = [
float(image_header["x_pixdim"]) * 10,
float(image_header["y_pixdim"]) * 10,
]
ds.PixelData = allframeslist[curframe].tostring()
output_file = os.path.join(export_path, image_file_name)
image.logger.info("Creating image: " + output_file)
ds.save_as(output_file)
curframe = curframe + 1
info_mask.SOPInstanceUID= instanceuid
info_mask.AccessionNumber=info.AccessionNumber
info_mask.Modality='SEG'
info_mask.Manufacturer='Stanford University'
info_mask.ManufacturerModelName= 'ePAD Matlab'
info_mask.DeviceSerialNumber='SN123456'
info_mask.SoftwareVersion='1.0'
info_mask.StudyInstanceUID=info.StudyInstanceUID
info_mask.SeriesInstanceUID= dicomuid
info_mask.SeriesNumber= 1000
info_mask.ContentDate=datetime.today().strftime('%Y%m%d')
info_mask.StudyDate=info.StudyDate
info_mask.SeriesDate=datetime.today().strftime('%Y%m%d')
info_mask.AcquisitionDate=datetime.today().strftime('%Y%m%d')
currentTime=datetime.today().strftime('%H%M%S.')
f = datetime.today().strftime('%f')
currentTime += str(f[0:3])
info_mask.ContentTime=currentTime
info_mask.StudyTime=info.StudyTime
info_mask.SeriesTime=currentTime
info_mask.AcquisitionTime=currentTime
info_mask.InstanceNumber= 1
info_mask.FrameOfReferenceUID= info.FrameOfReferenceUID
info_mask.PositionReferenceIndicator= ''
da1 = Dataset()
da2 = Dataset()
da3 = Dataset()
da4 = Dataset()
def saveDICOM_sliced_CT(image_np,
voxel_size,
image_position_patient,
output_path,
output_name,
orig_Z_pos=0,
patient_ID_in='SynthAttCorr_Test',
StudyInstanceUID='',
SeriesInstanceUID='',
TYPE_INT=np.int16,
vervose=True):
'''Saves a 3D numpy array as a CT DICOM file.
'''
# Get info type
info_bits = np.iinfo(TYPE_INT)
Vol_CT_max_val = np.max(image_np)
# Create output folder
OUTPUT_DCM_FOLDER = os.path.join(output_path, output_name)
File_mng.check_create_path('OUTPUT_DCM_FOLDER',
OUTPUT_DCM_FOLDER,
clear_folder=True)
# get current time
now = datetime.datetime.now()
# Number of slices to save
num_CT_slices = image_np.shape[Z]
# Save each slice
for idx_slice_CT in range(num_CT_slices):
print('Slice: %d/%d ' % (idx_slice_CT + 1, num_CT_slices),
end='')
print('', end='\r')
OUTPUT_DCM = os.path.join(OUTPUT_DCM_FOLDER, '%04d.dcm' % idx_slice_CT)
slice_aux = image_np[:, :, idx_slice_CT]
# This code was taken from the output of a valid CT file
# I do not know what the long dotted UIDs mean, but this code works...
file_meta = Dataset()
# (0008, 0016) SOP Class UID UI: CT Image Storage
file_meta.MediaStorageSOPClassUID = 'CT Image Storage'
# (0008, 0018) SOP Instance UID UI: 1.3.6.1.4.1.14519.5.2.1.3320.3273.139372384049551777032016175435
file_meta.MediaStorageSOPInstanceUID = '1.3.6.1.4.1.14519.5.2.1.3320.3273.139372384049551777032016175435'
# file_meta.ImplementationClassUID = '1.2.840.10008.5.1.4.1.1.20'
file_meta.TransferSyntaxUID = dicom.uid.ImplicitVRLittleEndian
ds = FileDataset(OUTPUT_DCM, {},
file_meta=file_meta,
preamble=b'\x00' * 128)
ds.Modality = 'CT'
ds.ContentDate = str(datetime.date.today()).replace('-', '')
ds.ContentTime = str(time.time()) #milliseconds since the epoch
# (0020, 000d) Study Instance UID UI: 1.3.6.1.4.1.14519.5.2.1.3320.3273.231445815234682119538863169983
if StudyInstanceUID == '':
StudyInstanceUID = '1.3.6.1.4.1.14519.5.2.1.3320.3273.231445815234682119538863169983'
ds.StudyInstanceUID = StudyInstanceUID
# (0020, 000e) Series Instance UID UI: 1.3.6.1.4.1.14519.5.2.1.3320.3273.330516103388011054891344582212
if SeriesInstanceUID == '':
SeriesInstanceUID = '1.3.6.1.4.1.14519.5.2.1.3320.3273.330516103388011054891344582212'
ds.SeriesInstanceUID = SeriesInstanceUID
# (0008, 1155) Referenced SOP Instance UID UI: 1.3.6.1.4.1.14519.5.2.1.3320.3273.275604822259752169794323488440
ds.SOPInstanceUID = '1.3.6.1.4.1.14519.5.2.1.3320.3273.2756048222597%d' % np.random.randint(
low=52169794323488440, high=92169794323488440)
# ds.SOPClassUID = '1.2.840.10008.5.1.4.1.1.20'
# These are the necessary imaging components of the FileDataset object.
# (0028, 0002) Samples per Pixel US: 1
ds.SamplesPerPixel = 1
# (0028, 0004) Photometric Interpretation CS: 'MONOCHROME2'
ds.PhotometricInterpretation = "MONOCHROME2"
# (0028, 0103) Pixel Representation US: 1
ds.PixelRepresentation = 1
# (0028, 0100) Bits Allocated US: 16
ds.BitsAllocated = 16
# (0028, 0101) Bits Stored US: 16
ds.BitsStored = 16
# (0028, 0102) High Bit US: 15
ds.HighBit = 15
# (0028, 0010) Rows US: 512
ds.Rows = slice_aux.shape[X]
# (0028, 0011) Columns US: 512
ds.Columns = slice_aux.shape[Y]
# (0028, 0030) Pixel Spacing DS: ['0.976562', '0.976562']
ds.PixelSpacing = [str(voxel_size[X]), str(voxel_size[Y])]
# (0018, 0088) Spacing Between Slices DS: "3.260000"
ds.SpacingBetweenSlices = b'00000'
# (0018, 0050) Slice Thickness DS: "1.250000"
ds.SliceThickness = str(voxel_size[Z])
ds.ImageOrientationPatient = [
'1.000000', '0.000000', '0.000000', '0.000000', '1.000000',
'0.000000'
]
ds.ImagePositionPatient = [
str(image_position_patient[X]).encode(),
str(image_position_patient[Y]).encode(),
str(orig_Z_pos + (idx_slice_CT * voxel_size[Z])).encode()
]
# Otros agregados
# (0008, 0050) Accession Number SH: ''
ds.AccessionNumber = ''
# (0008, 0022) Acquisition Date DA: '20001007'
ds.AcquisitionDate = now.strftime("%Y%m%d")
# (0008, 0032) Acquisition Time TM: '110409.543667'
ds.AcquisitionTime = now.strftime("%H%M%S")
# (0008, 0008) Image Type CS: ['ORIGINAL', 'PRIMARY', 'AXIAL']
ds.ImageType = ['ORIGINAL', 'PRIMARY', 'AXIAL']
# (0008, 0012) Instance Creation Date DA: '20001007'
ds.InstanceCreationDate = now.strftime("%Y%m%d")
# (0008, 0013) Instance Creation Time TM: '110451'
ds.InstanceCreationTime = now.strftime("%H%M%S")
# (0020, 0013) Instance Number IS: "207"
ds.InstanceNumber = str(idx_slice_CT)
ds.Manufacturer = 'UTN-UTT-CNEA-CONICET'
# (0010, 0020) Patient ID LO: 'C3N-02285'
ds.PatientID = patient_ID_in
# (0010, 0010) Patient's Name PN: 'C3N-02285'
ds.PatientName = output_name
# (0018, 5100) Patient Position CS: 'HFS'
ds.PatientPosition = 'HFS'
# (0018, 1030) Protocol Name LO: '4.1 PET_WB LOW BMI'
ds.ProtocolName = 'Synth. CT'
# (0018, 1100) Reconstruction Diameter DS: "500.000000"
ds.ReconstructionDiameter = '500.000000'
# (0008, 0090) Referring Physician's Name PN: ''
ds.ReferringPhysicianName = ''
# (0008, 0021) Series Date DA: '20001007'
ds.SeriesDate = now.strftime("%Y%m%d")
ds.SeriesNumber = ''
# (0008, 0031) Series Time TM: '110352'
ds.SeriesTime = now.strftime("%H%M%S")
# (0020, 1041) Slice Location DS: "-216.500"
ds.SliceLocation = str(orig_Z_pos + (idx_slice_CT * voxel_size[Z]))
# (0008, 0020) Study Date DA: '20001007'
ds.StudyDate = now.strftime("%Y%m%d")
# (0008, 1030) Study Description LO: 'PET WB LOW BMI'
ds.StudyDescription = 'synthetic CT created from NAC PET'
ds.StudyID = ''
# (0008, 0030) Study Time TM: '110246'
ds.StudyTime = now.strftime("%H%M%S")
# (0028, 1052) Rescale Intercept DS: "-1024"
ds.RescaleIntercept = "-1024"
# (0028, 1053) Rescale Slope DS: "1"
ds.RescaleSlope = "1" #str(Vol_CT_max_val/info_bits.max)
# (0028, 1054) Rescale Type LO: 'HU'
ds.RescaleType = 'HU'
# slice_aux = ((slice_aux/Vol_CT_max_val)*info_bits.max)+1024
# slice_aux = (((slice_aux+1024)/Vol_CT_max_val)*info_bits.max)
slice_aux = (slice_aux + 1024).astype(np.int16)
# print(slice_aux.max(),slice_aux.min())
# volume_aux = np.swapaxes(volume_aux,0,1)
# volume_aux = np.swapaxes(volume_aux,0,2)
ds.PixelData = slice_aux.tostring()
ds.save_as(OUTPUT_DCM)
print('done.')
return
