def determineScannerID(self, cs):
"""
Tries to identify machine model, used filter, and energy presentation
"""
dicomfields = [
["0008,1090", "ModelName"],
["0018,7050", "FilterMaterialLT"],
["0019,10C1",
"MICRODOSE IMAGE CONTENT"] #---: SUM FOR PRESENTATION
]
# 1. Try to id Scanner
cs.scannername = lit.stUnknown
dicomvalue = wadwrapper_lib.readDICOMtag(
dicomfields[0][0], cs.dcmInfile) # Manufacturer's Model Name
dicomvalue = str(dicomvalue).lower()
if dicomvalue.find("l50") > -1:
cs.scannername = lit.stL50
elif dicomvalue.find("lorad selenia") > -1:
cs.guessScanner = lit.stSelenia
elif dicomvalue.find("dimensions") > -1:
cs.guessScanner = lit.stDimensions
# 2. Try to id Filter
cs.filtername = wadwrapper_lib.readDICOMtag(dicomfields[1][0],
cs.dcmInfile) # Filtername
# 3. Try to id EnergyPresentation
cs.energypresentation = wadwrapper_lib.readDICOMtag(
dicomfields[2][0], cs.dcmInfile)
def determineScannerID(self,cs):
"""
Tries to identify machine model, used filter, and energy presentation
"""
dicomfields = [
["0008,1090", "ModelName"],
["0018,7050", "FilterMaterialLT"],
["0019,10C1", "MICRODOSE IMAGE CONTENT"] #---: SUM FOR PRESENTATION
]
# 1. Try to id Scanner
cs.scannername = lit.stUnknown
dicomvalue = wadwrapper_lib.readDICOMtag(dicomfields[0][0],cs.dcmInfile) # Manufacturer's Model Name
dicomvalue = str(dicomvalue).lower()
if dicomvalue.find("l50")>-1:
cs.scannername = lit.stL50
elif dicomvalue.find("lorad selenia")>-1:
cs.guessScanner = lit.stSelenia
elif dicomvalue.find("dimensions")>-1:
cs.guessScanner = lit.stDimensions
# 2. Try to id Filter
cs.filtername = wadwrapper_lib.readDICOMtag(dicomfields[1][0],cs.dcmInfile) # Filtername
# 3. Try to id EnergyPresentation
cs.energypresentation = wadwrapper_lib.readDICOMtag(dicomfields[2][0],cs.dcmInfile)
def DICOMInfo(cs, info='dicom', imslice=0):
"""
Return some characteristic information from the dicom headers
"""
if info == "dicom":
dicomfields = [
["0010,0010", "Patients Name"], # PIQT
["0018,1030", "Protocol Name"], # QA1S:MS,SE
["0008,0021", "Series Date"],
["0008,0031",
"Series Time"], # no ScanTime 0008,0032 in EnhancedDicom
["0018,1250", "Receive Coil Name"], # Q-Body
["0018,1251", "Transmit Coil Name"], # B
["0018,0095", "Pixel Bandwidth"], # 219
["0018,0020", "Scanning Sequence"], # SE
["0018,0021", "Scanning Variant"], # SS
["2005,1011", "Image_Type"], # M
["0018,0081", "Echo Time"], # 50
["0020,0012", "Acquisition Number"], # 5
["0018,0086", "Echo Number(s)"], # 1
["2001,1081", "Dyn_Scan_No"], # ?1
["0020,0013", "Instance Number"], # 1 slice no?
["2001,105f,2005,1079", "Dist_sel"], # -16.32
["2001,1083", "Central_freq"], # 63.895241 (MHz)
["0018,1020", "SoftwareVersions"],
]
results = []
for df in dicomfields:
key = df[0]
value = wadwrapper_lib.readDICOMtag(key, cs.dcmInfile, imslice)
if key == "0018,1020" and len(value) > 1:
value = '_'.join(value)
results.append((df[1], value))
return results
def DICOMInfo(self,cs,info='dicom'):
"""
Extract some info from the DICOM header. <info> is either 'dicom' (extensive list) or 'qc' (short list).
Returns list of <tag description>,<tag value>
"""
# Different from ImageJ version; tags "0008","0104" and "0054","0220"
# appear to be part of sequences. This gives problems (cannot be found
# or returning whole sequence blocks)
# Possibly this can be solved by using if(type(value) == type(dicom.sequence.Sequence()))
# but I don't see the relevance of these tags anymore, so set them to NO
self.determineScannerID(cs)
if(info == "dicom"):
dicomfields = [ ["0008,0021", "Series Date"],
["0008,0031", "Series Time"],
["0008,0070", "Manufacturer"],
["0008,0080", "InstitutionName"],
["0008,1010", "StationName"],
["0008,1030", "StudyDescription"],
["0008,103E", "SeriesDescription"],
["0008,1070", "Operator"],
["0010,0020", "PatientID"],
["0018,0060", "kVp"],
["0018,1000", "DeviceSerialNumber"],
["0018,1020", "SoftwareVersions"],
["0018,1110", "DistanceSourceToDetector"],
["0018,1111", "DistanceSourceToPatient"],
["0018,1150", "ExposureTime_(ms)"],
["0018,1151", "TubeCurrent_(mA)"],
["0018,1153", "muAs"],
["0018,1164", "ImagerPixelSpacing"],
["0018,1166", "Grid"],
["0018,1190", "FocalSpot"],
["0018,1191", "AnodeTargetMaterial"],
["0018,11A0", "BodyPartThickness"],
["0018,11A2", "CompressionForce"],
["0018,1405", "RelativeXRayExposure"],
["0018,700A", "DetectorID"],
["0018,700C", "DateOfLastDetectorCalibration"],
["0018,7050", "FilterMaterialLT"],
["0019,1029", "---"],
["0028,0101", "BitsStored"],
["0028,1040", "PixelensityRelationship"],
["0028,1052", "Rescaleercept"],
["0028,1053", "RescaleSlope"],
["0028,1054", "RescaleType"],
["0040,0302", "EntranceDose"],
["0040,0314", "HalfValueLayer_(mm)"],
["0040,0316", "OrganDose"],
["0040,8302", "EntranceDose_(mGy)"],
["0000,0000", "NOViewCodeSequence"],
["0000,0000", "NOViewCodeMeaning"]]
if cs.scannername == lit.stL50:
dicomfields[0] = ["0008,0022", "Acquisition Date"]
dicomfields[1] = ["0008,0030", "Acquisition Time"]
elif(info == "qc"):
dicomfields = [["0008,0021", "Series Date"],
["0008,1010", "StationName"],
["0008,1070", "Operator"],
["0018,0060", "kVp"],
["0018,1020", "SoftwareVersions"],
["0018,1030", "ProtocolName"],
["0018,1110", "DistanceSourceToDetector"],
["0018,1111", "DistanceSourceToPatient"],
["0018,1153", "muAs"],
["0018,1166", "Grid"],
["0018,1190", "FocalSpot"],
["0018,1191", "AnodeTargetMaterial"],
["0018,11A0", "BodyPartThickness"],
["0018,11A2", "CompressionForce"],
["0018,700A", "DetectorID"],
["0018,700C", "DateOfLastDetectorCalibration"],
["0018,7050", "FilterMaterialLT"],
["0040,0314", "HalfValueLayer_(mm)"],
["0040,0316", "OrganDose"],
["0040,8302", "EntranceDose_(mGy)"]]
if cs.scannername == lit.stL50:
dicomfields[0] = ["0008,0022", "Acquisition Date"]
dicomfields.append( ["0019,10c1", "EnergyComponent"] )
results = []
for df in dicomfields:
key = df[0]
value = ""
try:
value = wadwrapper_lib.readDICOMtag(key,cs.dcmInfile)
except:
value = ""
results.append( (df[1],value) )
return results
def DICOMInfo(self, cs, info='dicom'):
"""
Extract some info from the DICOM header. <info> is either 'dicom' (extensive list) or 'qc' (short list).
Returns list of <tag description>,<tag value>
"""
# Different from ImageJ version; tags "0008","0104" and "0054","0220"
# appear to be part of sequences. This gives problems (cannot be found
# or returning whole sequence blocks)
# Possibly this can be solved by using if(type(value) == type(dicom.sequence.Sequence()))
# but I don't see the relevance of these tags anymore, so set them to NO
self.determineScannerID(cs)
if (info == "dicom"):
dicomfields = [["0008,0021", "Series Date"],
["0008,0031", "Series Time"],
["0008,0070", "Manufacturer"],
["0008,0080", "InstitutionName"],
["0008,1010", "StationName"],
["0008,1030", "StudyDescription"],
["0008,103E", "SeriesDescription"],
["0008,1070", "Operator"],
["0010,0020", "PatientID"], ["0018,0060", "kVp"],
["0018,1000", "DeviceSerialNumber"],
["0018,1020", "SoftwareVersions"],
["0018,1110", "DistanceSourceToDetector"],
["0018,1111", "DistanceSourceToPatient"],
["0018,1150", "ExposureTime_(ms)"],
["0018,1151", "TubeCurrent_(mA)"],
["0018,1153", "muAs"],
["0018,1164", "ImagerPixelSpacing"],
["0018,1166", "Grid"], ["0018,1190", "FocalSpot"],
["0018,1191", "AnodeTargetMaterial"],
["0018,11A0", "BodyPartThickness"],
["0018,11A2", "CompressionForce"],
["0018,1405", "RelativeXRayExposure"],
["0018,700A", "DetectorID"],
["0018,700C", "DateOfLastDetectorCalibration"],
["0018,7050", "FilterMaterialLT"],
["0019,1029", "---"], ["0028,0101", "BitsStored"],
["0028,1040", "PixelensityRelationship"],
["0028,1052", "Rescaleercept"],
["0028,1053", "RescaleSlope"],
["0028,1054", "RescaleType"],
["0040,0302", "EntranceDose"],
["0040,0314", "HalfValueLayer_(mm)"],
["0040,0316", "OrganDose"],
["0040,8302", "EntranceDose_(mGy)"],
["0000,0000", "NOViewCodeSequence"],
["0000,0000", "NOViewCodeMeaning"]]
if cs.scannername == lit.stL50:
dicomfields[0] = ["0008,0022", "Acquisition Date"]
dicomfields[1] = ["0008,0030", "Acquisition Time"]
elif (info == "qc"):
dicomfields = [["0008,0021", "Series Date"],
["0008,1010", "StationName"],
["0008,1070", "Operator"], ["0018,0060", "kVp"],
["0018,1020", "SoftwareVersions"],
["0018,1030", "ProtocolName"],
["0018,1110", "DistanceSourceToDetector"],
["0018,1111", "DistanceSourceToPatient"],
["0018,1153", "muAs"], ["0018,1166", "Grid"],
["0018,1190", "FocalSpot"],
["0018,1191", "AnodeTargetMaterial"],
["0018,11A0", "BodyPartThickness"],
["0018,11A2", "CompressionForce"],
["0018,700A", "DetectorID"],
["0018,700C", "DateOfLastDetectorCalibration"],
["0018,7050", "FilterMaterialLT"],
["0040,0314", "HalfValueLayer_(mm)"],
["0040,0316", "OrganDose"],
["0040,8302", "EntranceDose_(mGy)"]]
if cs.scannername == lit.stL50:
dicomfields[0] = ["0008,0022", "Acquisition Date"]
dicomfields.append(["0019,10c1", "EnergyComponent"])
results = []
for df in dicomfields:
key = df[0]
value = ""
try:
value = wadwrapper_lib.readDICOMtag(key, cs.dcmInfile)
except:
value = ""
results.append((df[1], value))
return results
def sfnrTest(data,results,params):
"""
MRI_fBIRN Checks: fBIRN QA
Signal-to-Fluctuation-Noise Ratio (SFNR)
... (more tests to come eventually)
Workflow:
1. Read image or sequence
2. Run test
3. Build output
"""
#(1) Reads input file(s) list as a series (scan) single DICOM object
# returns DICOM header, raw pizelData object scaled and type of current DICOM object { 2D, 3D, ... }
#dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=False,logTag=logTag())
#------------------------------------------------------------------
pixeldataIn = None
if ( len(data.series_filelist[0]) > 1 ) or ( len(data.series_filelist[0]) == 1 and os.path.isdir(data.series_filelist[0][0]) ):
fileList = data.series_filelist[0]
if len(data.series_filelist[0]) == 1 :
fileList = data.series_filelist[0][0]
# read/load a list of DICOM files
seriesDataList = pydicom_series.read_files(fileList,showProgress=True, readPixelData=True,skipNonImageFiles=True)
# check number of series in the array/list
if len(seriesDataList) != 1:
raise ValueError("{} Such test is supposed to apply solely to a single series/scan. Something went wrong...".format(logTag))
seriesData = seriesDataList[0]
nTemporalPositions = int(seriesData.info["0020","0105"].value)
# Image pixeldata seems to be transposed when read using wadwrapper_lib methods...
pixeldataIn = seriesData.get_pixel_array()
pixeldataIn = np.transpose(pixeldataIn)
new3rdDimension = int(pixeldataIn.shape[2])/nTemporalPositions
print '[Debug] Image dimensions: ' + str(pixeldataIn.shape)
print '[Debug] New dimensions: (%s, %s, %s, %s)' %(str(pixeldataIn.shape[0]),str(pixeldataIn.shape[1]),str(new3rdDimension),str(nTemporalPositions))
pixeldataIn = np.reshape(pixeldataIn, (pixeldataIn.shape[0],pixeldataIn.shape[1],new3rdDimension,nTemporalPositions))
elif ( len(data.series_filelist[0]) == 1) and ( wadwrapper_lib.testIfEnhancedDICOM(data.series_filelist[0][0]) ):
# read/load a single DICOM file
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareEnhancedInput(data.series_filelist[0][0],headers_only=False)
# DICOM keeps NumberOfTemporalPositions nested in sequence items/subitems. And DCM4CHEE seems not to keep them at all (!?).
# Workaround: Use Philips private tag, should be read as a bit string and converted to string/integer/whatever
if 'PHILIPS' not in (wadwrapper_lib.readDICOMtag("0008,0070",dcmInfile)).upper():
raise ValueError("{} Input enhanced dataset type not suitable --> no dynamics/temporal information found".format(logTag))
nSlicesRaw = wadwrapper_lib.readDICOMtag("2001,1018",dcmInfile)
try:
nSlices = struct.unpack("<L",nSlicesRaw)[0]
except:
nSlices = nSlicesRaw
nTemporalPositions = int(pixeldataIn.shape[0])/int(nSlices)
# Image pixeldata seems to be transposed when read using wadwrapper_lib methods...
pixeldataIn = np.transpose(pixeldataIn)
new3rdDimension = int(pixeldataIn.shape[2])/nTemporalPositions
print '[Debug] Image dimensions: ' + str(pixeldataIn.shape)
print '[Debug] New dimensions: (%s, %s, %s, %s)' %(str(pixeldataIn.shape[0]),str(pixeldataIn.shape[1]),str(new3rdDimension),str(nTemporalPositions))
pixeldataIn = np.reshape(pixeldataIn, (pixeldataIn.shape[0],pixeldataIn.shape[1],new3rdDimension,nTemporalPositions))
else:
raise ValueError("{} Input dataset type cannot be determined or is not compatible".format(logTag))
#(2)
#if 'BIRN' not in options['seriesDesc'] or 'BIRN' not in options['protocolName']:
# raise ValueError("{} Input dataset type not suitable".format(logTag))
# OR
# print '[Warning] Not an fBIRN scan --> do nothing'
#Check if pixeldataIn is actually a numpy array
if type(pixeldataIn).__module__ != np.__name__ :
raise ValueError("{} Unable to pull out the pixel data of the incomming DICOM file(s)".format(logTag))
output = fBIRN_lib.fBIRN_SFNR(pixeldataIn,plot_data=False)
#(3)
results.addFloat('mean_SNR', np.mean(output['imgsnr']), quantity='SNR', level=2) #quantity is actually magnitude in the WAD-QC app
results.addFloat('mean_SFNR', output['meansfnr'], quantity='SFNR', level=2) #quantity is actually magnitude in the WAD-QC app
#print '[info] SNR, %f'%np.mean(output['imgsnr'])
#print '[info] SFNR, %f'%output['meansfnr']
#print '[info] drift, %f'%output['trend'].params[1]
#if len(output['spikes']) > 0:
#print '[info] nspikes,%d'%len(output['spikes'])
if len(output['spikes']) > 0:
results.addBool('spikes', True, level=2) #Spikes detected
else :
results.addBool('spikes', False, level=2) #No spikes detected
def sfnrTest(data, results, params):
"""
MRI_fBIRN Checks: fBIRN QA
Signal-to-Fluctuation-Noise Ratio (SFNR)
... (more tests to come eventually)
Workflow:
1. Read image or sequence
2. Run test
3. Build output
"""
#(1) Reads input file(s) list as a series (scan) single DICOM object
# returns DICOM header, raw pizelData object scaled and type of current DICOM object { 2D, 3D, ... }
#dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=False,logTag=logTag())
#------------------------------------------------------------------
pixeldataIn = None
if (len(data.series_filelist[0]) > 1) or (len(data.series_filelist[0]) == 1
and os.path.isdir(
data.series_filelist[0][0])):
fileList = data.series_filelist[0]
if len(data.series_filelist[0]) == 1:
fileList = data.series_filelist[0][0]
# read/load a list of DICOM files
seriesDataList = pydicom_series.read_files(fileList,
showProgress=True,
readPixelData=True,
skipNonImageFiles=True)
# check number of series in the array/list
if len(seriesDataList) != 1:
raise ValueError(
"{} Such test is supposed to apply solely to a single series/scan. Something went wrong..."
.format(logTag))
seriesData = seriesDataList[0]
nTemporalPositions = int(seriesData.info["0020", "0105"].value)
# Image pixeldata seems to be transposed when read using wadwrapper_lib methods...
pixeldataIn = seriesData.get_pixel_array()
pixeldataIn = np.transpose(pixeldataIn)
new3rdDimension = int(pixeldataIn.shape[2]) / nTemporalPositions
print '[Debug] Image dimensions: ' + str(pixeldataIn.shape)
print '[Debug] New dimensions: (%s, %s, %s, %s)' % (
str(pixeldataIn.shape[0]), str(pixeldataIn.shape[1]),
str(new3rdDimension), str(nTemporalPositions))
pixeldataIn = np.reshape(pixeldataIn,
(pixeldataIn.shape[0], pixeldataIn.shape[1],
new3rdDimension, nTemporalPositions))
elif (len(data.series_filelist[0])
== 1) and (wadwrapper_lib.testIfEnhancedDICOM(
data.series_filelist[0][0])):
# read/load a single DICOM file
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareEnhancedInput(
data.series_filelist[0][0], headers_only=False)
# DICOM keeps NumberOfTemporalPositions nested in sequence items/subitems. And DCM4CHEE seems not to keep them at all (!?).
# Workaround: Use Philips private tag, should be read as a bit string and converted to string/integer/whatever
if 'PHILIPS' not in (wadwrapper_lib.readDICOMtag(
"0008,0070", dcmInfile)).upper():
raise ValueError(
"{} Input enhanced dataset type not suitable --> no dynamics/temporal information found"
.format(logTag))
nSlicesRaw = wadwrapper_lib.readDICOMtag("2001,1018", dcmInfile)
try:
nSlices = struct.unpack("<L", nSlicesRaw)[0]
except:
nSlices = nSlicesRaw
nTemporalPositions = int(pixeldataIn.shape[0]) / int(nSlices)
# Image pixeldata seems to be transposed when read using wadwrapper_lib methods...
pixeldataIn = np.transpose(pixeldataIn)
new3rdDimension = int(pixeldataIn.shape[2]) / nTemporalPositions
print '[Debug] Image dimensions: ' + str(pixeldataIn.shape)
print '[Debug] New dimensions: (%s, %s, %s, %s)' % (
str(pixeldataIn.shape[0]), str(pixeldataIn.shape[1]),
str(new3rdDimension), str(nTemporalPositions))
pixeldataIn = np.reshape(pixeldataIn,
(pixeldataIn.shape[0], pixeldataIn.shape[1],
new3rdDimension, nTemporalPositions))
else:
raise ValueError(
"{} Input dataset type cannot be determined or is not compatible".
format(logTag))
#(2)
#if 'BIRN' not in options['seriesDesc'] or 'BIRN' not in options['protocolName']:
# raise ValueError("{} Input dataset type not suitable".format(logTag))
# OR
# print '[Warning] Not an fBIRN scan --> do nothing'
#Check if pixeldataIn is actually a numpy array
if type(pixeldataIn).__module__ != np.__name__:
raise ValueError(
"{} Unable to pull out the pixel data of the incomming DICOM file(s)"
.format(logTag))
output = fBIRN_lib.fBIRN_SFNR(pixeldataIn, plot_data=False)
#(3)
results.addFloat(
'mean_SNR', np.mean(output['imgsnr']), quantity='SNR',
level=2) #quantity is actually magnitude in the WAD-QC app
results.addFloat(
'mean_SFNR', output['meansfnr'], quantity='SFNR',
level=2) #quantity is actually magnitude in the WAD-QC app
#print '[info] SNR, %f'%np.mean(output['imgsnr'])
#print '[info] SFNR, %f'%output['meansfnr']
#print '[info] drift, %f'%output['trend'].params[1]
#if len(output['spikes']) > 0:
#print '[info] nspikes,%d'%len(output['spikes'])
if len(output['spikes']) > 0:
results.addBool('spikes', True, level=2) #Spikes detected
else:
results.addBool('spikes', False, level=2) #No spikes detected
def readDICOMtag(self, cs_mam, key, imslice=0): # slice=2 is image 3
value = wadwrapper_lib.readDICOMtag(key, cs_mam.dcmInfile, imslice)
return value
def readDICOMtag(self,cs_mam,key,imslice=0): # slice=2 is image 3
value = wadwrapper_lib.readDICOMtag(key,cs_mam.dcmInfile,imslice)
return value
