def setup_series(inputfile, params, headers_only):
"""
Shared routine to set runtime parameters and build structure
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
"""
# 1. Set runtime parameters
# 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=headers_only, logTag=logTag())
# 3. Build and populate qcstructure
qclib = QCUS_lib.US_QC(guimode=False)
cs = QCUS_lib.USStruct(dcmInfile, pixeldataIn, dicomMode)
cs.verbose = False # do not produce detailed logging
cs.uni_filter = int(params.find("uni_filter").text)
cs.uni_delta = float(params.find("uni_delta").text)
cs.uni_low = float(params.find("uni_low").text)
cs.sen_filter = int(params.find("sen_filter").text)
cs.sen_delta = float(params.find("sen_delta").text)
cs.ver_offset = int(params.find("ver_offset").text)
cs.hor_offset = int(params.find("hor_offset").text)
cs.fitcircle_frac = float(params.find("fitcircle_frac").text)
cs.cluster_fminsize = float(params.find("cluster_fminsize").text)
try:
cs.verbose = params.find('verbose').text.lower() in [
'1', 'true', 'y', 'yes'
]
except:
pass
return qclib, cs
def cdmamsetup_series(inputfile, params, headers_only):
"""
Shared routine to set runtime parameters and build structure
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
"""
# 1. Set runtime parameters
if not headers_only: # then we can skip the parameter check
try:
phantomversion = params.find("phantomversion").text
except AttributeError:
raise ValueError(logTag() + " missing phantomversion parameter!")
try:
modeCDCOM = (params.find("modeCDCOM").text == 'True')
except AttributeError:
raise ValueError(logTag() + " missing cdcommode parameter!")
else:
phantomversion = '3.2' # dummy for headers
modeCDCOM = False
# 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=headers_only, logTag=logTag())
# 3. Build and populate qcstructure
qclib = CDMam_lib.CDMam()
cs = CDMam_lib.CDMamStruct(dcmInfile, pixeldataIn, phantomversion)
cs.imnum = 0 # needs to be set to an increasing number if multiple files are used
cs.verbose = False # do not produce detailed logging
cs.imageFileName = inputfile[0] # only for CDCOM.exe
qclib.determineScannerID(cs)
return qclib, cs, modeCDCOM
def cdmamsetup_series(inputfile,params,headers_only):
"""
Shared routine to set runtime parameters and build structure
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
"""
# 1. Set runtime parameters
if not headers_only: # then we can skip the parameter check
try:
phantomversion = params.find("phantomversion").text
except AttributeError:
raise ValueError(logTag()+" missing phantomversion parameter!")
try:
modeCDCOM = (params.find("modeCDCOM").text == 'True')
except AttributeError:
raise ValueError(logTag()+" missing cdcommode parameter!")
else:
phantomversion = '3.2' # dummy for headers
modeCDCOM = False
# 2. Check data format
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(inputfile,headers_only=headers_only,logTag=logTag())
# 3. Build and populate qcstructure
qclib = CDMam_lib.CDMam()
cs = CDMam_lib.CDMamStruct(dcmInfile,pixeldataIn,phantomversion)
cs.imnum = 0 # needs to be set to an increasing number if multiple files are used
cs.verbose = False # do not produce detailed logging
cs.imageFileName = inputfile[0] # only for CDCOM.exe
qclib.determineScannerID(cs)
return qclib,cs,modeCDCOM
def setup_series(inputfile, params, headers_only):
"""
Shared routine to set runtime parameters and build structure
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
"""
# 1. Set runtime parameters
"""
if not headers_only: # then we can skip the parameter check
try:
phantomversion = params.find("phantomversion").text
except AttributeError:
raise ValueError(logTag()+" missing phantomversion parameter!")
try:
modeCDCOM = (params.find("modeCDCOM").text == 'True')
except AttributeError:
raise ValueError(logTag()+" missing cdcommode parameter!")
else:
phantomversion = '3.2' # dummy for headers
modeCDCOM = False
"""
# 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=headers_only, logTag=logTag())
# 3. Build and populate qcstructure
qclib = QCUS_lib.US_QC(guimode=False)
cs = QCUS_lib.USStruct(dcmInfile, pixeldataIn, dicomMode)
cs.verbose = False # do not produce detailed logging
return qclib, cs
def setup_series(inputfile,params,headers_only):
"""
Shared routine to set runtime parameters and build structure
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
"""
# 1. Set runtime parameters
"""
if not headers_only: # then we can skip the parameter check
try:
phantomversion = params.find("phantomversion").text
except AttributeError:
raise ValueError(logTag()+" missing phantomversion parameter!")
try:
modeCDCOM = (params.find("modeCDCOM").text == 'True')
except AttributeError:
raise ValueError(logTag()+" missing cdcommode parameter!")
else:
phantomversion = '3.2' # dummy for headers
modeCDCOM = False
"""
# 2. Check data format
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(inputfile,headers_only=headers_only,logTag=logTag())
# 3. Build and populate qcstructure
qclib = QCUS_lib.US_QC(guimode=False)
cs = QCUS_lib.USStruct(dcmInfile,pixeldataIn,dicomMode)
cs.verbose = False # do not produce detailed logging
return qclib,cs
def xrayqc_series(data, results, params):
"""
QCXRay_UMCU checks:
Horizontal uniformity
XRayEdges
LowContrast
DynamicRange
MTF
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qclib = QCXRay_lib.XRayQC()
room = _getRoomDefinition(params)
cs = QCXRay_lib.XRayStruct(dcmInfile, pixeldataIn, room)
cs.verbose = False # do not produce detailed logging
## 4. Run tests
error, msg = qclib.QC(cs)
## 5. Build xml output
## Struct now contains all the results and we can write these to the WAD IQ database
stand = qclib.TableOrWall(cs)
idname = '_' + stand
labvals = qclib.ReportEntries(cs)
tmpdict = {}
for elem in labvals:
#labvals.append( {'name':'label','value':0, 'quantity':'columnname','level':'1:default, 2: detail','pos':missing or a number} )
# if no pos given, the next one will be given
# if no quantity given, 'name' will be used
# if no level given, the default will be used
quan = elem['quantity'] if 'quantity' in elem else str(elem['name'])
level = elem['level'] if 'level' in elem else None
rank = elem['rank'] if 'rank' in elem else None
results.addFloat(elem['name'] + str(idname),
elem['value'],
quantity=quan,
level=level,
rank=rank)
## 6. Build artefact picture thumbnail
filename = 'test' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename)
results.addObject('AnnotatedImage' + idname, filename)
def xrayqc_uniformity_series(data, results, params):
"""
n13_uniformity checks:
Uniformity
Artefacts
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(inputfile,headers_only=False,logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qclib = n13_lib.XRayQC()
room = _getRoomDefinition(params)
cs = n13_lib.XRayStruct(dcmInfile,pixeldataIn,room)
cs.verbose = False # do not produce detailed logging
## 4. Run tests
error,msg = qclib.QCUnif(cs)
## 5. Build xml output
## Struct now contains all the results and we can write these to the WAD IQ database
if not cs.DetectorSuffix() is None:
idname = '_'+cs.DetectorSuffix()
else:
idname = ''
## First Build artefact picture thumbnail
label = 'unif'
filename = '%s%s.jpg'%(label,idname) # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs,filename, 'artefacts')
results.addObject('%s%s'%(label,idname),filename)
labvals = qclib.ReportEntries(cs)
tmpdict={}
for elem in labvals:
#labvals.append( {'name':'label','value':0, 'quantity':'columnname','level':'1:default, 2: detail','pos':missing or a number} )
# if no pos given, the next one will be given
# if no quantity given, 'name' will be used
# if no level given, the default will be used
quan = elem['quantity'] if 'quantity' in elem else str(elem['name'])
level = elem['level'] if 'level' in elem else None
rank = elem['rank'] if 'rank' in elem else None
results.addFloat(elem['name']+str(idname), elem['value'], quantity=quan, level=level,rank=rank)
def xrayqc_series(data, results, params):
"""
QCXRay_UMCU checks:
Horizontal uniformity
XRayEdges
LowContrast
DynamicRange
MTF
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qclib = QCXRay_lib.XRayQC()
room = _getRoomDefinition(params)
cs = QCXRay_lib.XRayStruct(dcmInfile, pixeldataIn, room)
cs.verbose = False # do not produce detailed logging
## 4. Run tests
error, msg = qclib.QC(cs)
## 5. Build xml output
## Struct now contains all the results and we can write these to the WAD IQ database
stand = qclib.TableOrWall(cs)
idname = '_' + stand
labvals = qclib.ReportEntries(cs)
tmpdict = {}
for key, val in labvals:
results.addFloat(key + str(idname), val, quantity=str(key))
## 6. Build artefact picture thumbnail
filename = 'test' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename)
results.addObject('AnnotatedImage' + idname, filename)
def xrayqc_series(data, results, params):
"""
QCXRay_UMCU checks:
Horizontal uniformity
XRayEdges
LowContrast
DynamicRange
MTF
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(inputfile,headers_only=False,logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qclib = QCXRay_lib.XRayQC()
room = _getRoomDefinition(params)
cs = QCXRay_lib.XRayStruct(dcmInfile,pixeldataIn,room)
cs.verbose = False # do not produce detailed logging
## 4. Run tests
error,msg = qclib.QC(cs)
## 5. Build xml output
## Struct now contains all the results and we can write these to the WAD IQ database
stand = qclib.TableOrWall(cs)
idname = '_'+stand
labvals = qclib.ReportEntries(cs)
tmpdict={}
for key,val in labvals:
results.addFloat(key+str(idname), val, quantity=str(key))
## 6. Build artefact picture thumbnail
filename = 'test'+idname+'.jpg' # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs,filename)
results.addObject('AnnotatedImage'+idname,filename)
def ctheader_series(data, results, params):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
info = 'dicom'
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=True, logTag=logTag())
qcctlib = QCCT_lib.CT_QC()
cs = QCCT_lib.CTStruct(dcmInfile=dcmInfile,
pixeldataIn=pixeldataIn,
dicomMode=dicomMode)
cs.verbose = False
error = qcctlib.HeadOrBody(cs)
if (error == True or cs.anatomy == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine Anatomy".format(logTag))
result_dict = {}
idname = ""
if cs.anatomy == lit.stHead:
idname = "_H"
else:
idname = "_B"
# only uncomment if same config used for all scanners: idname += "_"+cs.guessScanner.name
## 1. Run tests
dicominfo = qcctlib.DICOMInfo(cs, info)
## 2. Add results to 'result' object
# plugionversion is newly added in for this plugin since pywad2
results.addChar('pluginversion' + idname, str(
qcctlib.qcversion)) # do not specify level, use default from config
results.addChar('Anatomy', str(
cs.anatomy)) # do not specify level, use default from config
for di in dicominfo:
results.addChar(di[0] + idname,
str(di[1])[:min(len(str(di[1])), 128)]
) # do not specify level, use default from config
def header_series(data, results, **kwargs):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Read only headers
2. Run tests
3. Build xml output
"""
info = 'qc'
## 1. read only headers
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=True, logTag=logTag())
## 2. Run tests
qclib = QCDDL_lib.DDLQC()
## Table or Wall? from distances and sensitivity; for well defined protocols to be defined in DESCRIPTION field
cs = QCDDL_lib.DDLStruct(dcmInfile, None, dicomMode)
cs.verbose = False # do not produce detailed logging
dicominfo = qclib.DICOMInfo(cs, info)
idname = '_' + qclib.HorizontalOrVertical(cs)
## 3. Build xml output
floatlist = []
results.addChar('pluginversion' + idname, str(
qclib.qcversion)) # do not specify level, use default from config
for di in dicominfo:
if di[0] in floatlist:
results.addFloat(
di[0] + idname,
di[1]) # do not specify level, use default from config
else:
results.addChar(di[0] + idname,
str(di[1])[:min(len(str(di[1])), 128)]
) # do not specify level, use default from config
results.addChar(
'room' + idname,
cs.guessroom.name) # do not specify level, use default from config
results.addChar('stand' + idname, qclib.HorizontalOrVertical(
cs)) # do not specify level, use default from config
def qc_series(data, results, **kwargs):
"""
QCDDL_UMCU checks:
Horizontal uniformity
LowContrast
DynamicRange
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
## 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=False, logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qclib = QCDDL_lib.DDLQC()
cs = QCDDL_lib.DDLStruct(dcmInfile, pixeldataIn, dicomMode)
cs.verbose = False # do not produce detailed logging
## 4. Run tests
error, msg = qclib.QC(cs)
## 5. Build xml output
## Struct now contains all the results and we can write these to the WAD IQ database
stand = qclib.HorizontalOrVertical(cs)
idname = '_' + stand
labvals = qclib.ReportEntries(cs)
tmpdict = {}
for key, val in labvals:
results.addFloat(key + str(idname), val, quantity=str(key))
## 6. Build artefact picture thumbnail
filename = 'test' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename)
results.addObject('AnnotatedImage' + idname, filename)
def ctheader_series(data,results,params):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
info = 'dicom'
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=True,logTag=logTag())
qcctlib = QCCT_lib.CT_QC()
cs = QCCT_lib.CTStruct(dcmInfile=dcmInfile,pixeldataIn=pixeldataIn,dicomMode=dicomMode)
cs.verbose = False
error = qcctlib.HeadOrBody(cs)
if(error == True or cs.anatomy == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine Anatomy".format(logTag))
result_dict = {}
idname = ""
if cs.anatomy == lit.stHead:
idname = "_H"
else:
idname = "_B"
# only uncomment if same config used for all scanners: idname += "_"+cs.guessScanner.name
## 1. Run tests
dicominfo = qcctlib.DICOMInfo(cs,info)
## 2. Add results to 'result' object
# plugionversion is newly added in for this plugin since pywad2
results.addChar('pluginversion'+idname, str(qcctlib.qcversion)) # do not specify level, use default from config
results.addChar('Anatomy', str(cs.anatomy)) # do not specify level, use default from config
for di in dicominfo:
results.addChar(di[0]+idname, str(di[1])[:min(len(str(di[1])),128)]) # do not specify level, use default from config
def mammoqc_series(data, results, **kwargs):
"""
QCMammo_UMCU checks:
Uniformity (5 rois) and SNR (hologic),
DoseRatio (empirical/calculated from DICOM)
Artefacts (spots, dead pixels)
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(inputfile, headers_only=False, logTag=logTag())
### try:
### dcmInfile = dicom.read_file(inputfile)
### pixeldataIn = dcmInfile.pixel_array.transpose() # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
### except:
### print logTag()+"could not open dicomfile!"
### sys.exit()
## 3. Build and populate qcstructure
remark = ""
qcmammolib = QCMammo_lib.Mammo_QC()
cs_mam = QCMammo_lib.MammoStruct(dcmInfile, pixeldataIn)
cs_mam.verbose = False # do not produce detailed logging
if qcmammolib.NeedsCropping(cs_mam):
cs_mam.expertmode = True
qcmammolib.RestrictROI(cs_mam)
remark = "CROPPED"
## 4. Run tests
# Uniformity check
error = qcmammolib.Uniformity(cs_mam)
if error:
remark += "/ERROR_UNIFORMITY"
# Contrast L50
error = qcmammolib.L50Contrast(cs_mam) # doesn't do anything if not L50
if error:
remark += "/ERROR_L50CONTRAST"
# Dose Ratio
error = qcmammolib.DoseRatio(cs_mam)
if error:
remark += "/ERROR_DOSERATIO"
# Artefacts
error = qcmammolib.Artefacts(cs_mam)
if error:
remark += "/ERROR_ARTEFACTS"
## 5. Build xml output
## Struct now contains all the results and we can write these to the
## WAD IQ database
includedlist = ["unif_pct", "snr_hol", "doseratio", "art_clusters", "expert_inoutoverin", "contrast_snr"]
excludedlist = [
"verbose",
"dcmInfile",
"pixeldataIn",
"hasmadeplots",
"means",
"stdevs",
"unif",
"snr_hol",
"unif_rois",
"doseratio",
"art_clusters",
"art_image",
"art_borderpx",
"art_threshold",
"art_rois",
"expertmode",
"expert_roipts",
"expert_frac",
"expert_inoutoverin",
"filtername",
"scannername",
"contrast_rois",
"contrast_mean",
"contrast_sd",
]
idname = "_" + cs_mam.filtername
if "SUMPRES" in idname:
idname = "" # only one image
results.addChar("NOTE" + idname, remark)
for elem in cs_mam.__dict__:
if elem in includedlist:
newkeys = []
newvals = []
try:
elemval = cs_mam.__dict__[elem]
if "contrast_snr" in elem: # array
for ix, snr in enumerate(elemval):
newkeys.append("CNR" + str(ix))
newvals.append(snr)
elif "art_clusters" in elem:
newkeys.append(str(elem))
newvals.append(len(elemval))
else:
newkeys.append(str(elem))
newvals.append(elemval)
except:
print logTag() + "error for", elem
tmpdict = {}
for key, val in zip(newkeys, newvals):
results.addFloat(key + str(idname), val, quantity=str(key))
## 6. Build artefact picture thumbnail
filename = "test" + idname + ".jpg" # Use jpg if a thumbnail is desired
# object_naam_pad = outputfile.replace('result.xml','test'+idname+'.jpg') # Use jpg if a thumbnail is desired
qcmammolib.saveAnnotatedArtefactImage(cs_mam, filename)
results.addObject("ArtefactImage" + idname, filename)
def ctqc_series(data,results,params):
"""
QCCT_UMCU Checks: extension of Philips QuickIQ (also for older scanners without that option), for both Head and Body if provided
Uniformity
HU values
Noise
Linearity
Workflow:
1. Read image or sequence
2. Run test
3. Build xml output
"""
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=False,logTag=logTag())
qclib = QCCT_lib.CT_QC()
cs = QCCT_lib.CTStruct(dcmInfile=dcmInfile,pixeldataIn=pixeldataIn,dicomMode=dicomMode)
cs.forceScanner = _getScannerDefinition(params)
cs.verbose = False
## id scanner
error = qclib.DetermineCTID(cs)
if(error == True or cs.guessScanner.name == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine CT ID".format(logTag))
error = qclib.HeadOrBody(cs)
if(error == True or cs.anatomy == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine Anatomy".format(logTag))
idname = ""
if cs.anatomy == lit.stHead:
idname = "_H"
else:
idname = "_B"
# only uncomment if same config used for all scanners: idname += cs.guessScanner.name
## 2. Run tests
error = qclib.AnalyseCT(cs)
if error:
raise ValueError("{} ERROR! Error in AnalyseCT".format(logTag))
## Struct now contains all the results and we can write these to the
## WAD IQ database
includedlist = [
'roiavg',
'roisd',
'snr_hol',
'unif',
'linearity',
'maxdev',
'shiftxypx',
]
excludedlist = [
'verbose',
'dcmInfile',
'pixeldataIn',
'dicomMode',
'hasmadeplots',
'guessScanner',
'anatomy',
'roiavg',
'roisd',
'snr_hol',
'unif',
'linearity',
'maxdev',
'shiftxypx',
'valid'
'skull_avg',
'unif_slice',
'unif_rois'
]
for elem in cs.__dict__:
if elem in includedlist:
newkeys = []
newvals = []
try:
elemval = cs.__dict__[elem]
if 'roiavg' in elem: # array of avgs
newkeys.append('MeanCenter')
newvals.append(elemval[0])
newkeys.append('MeanAir')
newvals.append(elemval[3])
elif 'shiftxypx' in elem:
newkeys.append('shiftxpx')
newvals.append(elemval[0])
newkeys.append('shiftypx')
newvals.append(elemval[1])
else:
newkeys.append(str(elem))
newvals.append(elemval)
except:
print logTag()+"error for",elem
elemval = -1.
for key,val in zip(newkeys,newvals):
results.addFloat(key+str(idname), val, quantity=str(key))
## Build thumbnail
filename = 'test'+idname+'.jpg' # Use jpg if a thumbnail is desired
if cs.dicomMode == wadwrapper_lib.stMode2D:
scipy.misc.imsave(filename,cs.pixeldataIn.transpose()) # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
else:
scipy.misc.imsave(filename,(cs.pixeldataIn[cs.unif_slice]).transpose()) # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
results.addObject('CTslice'+idname,filename)
def ocr_series(data, results, params):
"""
Use pyOCR which for OCR
returns rect rois for plotting in overview
"""
inputfile = data.series_filelist[0] # give me a [filename]
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag())
rectrois = []
error = False
msg = ''
# solve ocr params
regions = {}
for param in params:
#'OCR_TissueIndex.xywh' = 'x;y;w;h'
#'OCR_TissueIndex.prefix' = 'prefix'
#'OCR_TissueIndex.suffix' = 'suffix'
if param.tag.startswith('OCR_'):
split = param.tag.find('.') # ':' is illegal in xml names
name = param.tag[:split]
stuff = param.tag[split + 1:]
if not name in regions:
regions[name] = {'prefix': '', 'suffix': ''}
if stuff == 'xywh':
regions[name]['xywh'] = [int(p) for p in param.text.split(';')]
elif stuff == 'prefix':
regions[name]['prefix'] = param.text
elif stuff == 'suffix':
regions[name]['suffix'] = param.text
elif stuff == 'type':
regions[name]['type'] = param.text
for name, region in regions.items():
rectrois.append([(region['xywh'][0], region['xywh'][1]),
(region['xywh'][0] + region['xywh'][2],
region['xywh'][1] + region['xywh'][3])])
txt, part = ocr_lib.OCR(pixeldataIn, region['xywh'])
if region['type'] == 'object':
import scipy
im = scipy.misc.toimage(part)
fn = '%s.jpg' % name
im.save(fn)
results.addObject(name, fn)
else:
try:
value = ocr_lib.txt2type(txt, region['type'], region['prefix'],
region['suffix'])
if region['type'] == 'float':
results.addFloat(name, value)
elif region['type'] == 'string':
results.addChar(name, value)
elif region['type'] == 'bool':
results.addBool(name, value)
except:
error = True
msg += name + ' '
return rectrois, error, msg
def mrheader_series(data, results, **kwargs):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
info = 'dicom'
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=True, logTag=logTag())
qclib = QCMR_lib.PiQT_QC()
cs = QCMR_lib.PiQT_Struct(dcmInfile=dcmInfile,
pixeldataIn=pixeldataIn,
dicomMode=dicomMode,
piqttest=None)
cs.verbose = False
## id scanner
idname = ""
error = qclib.DetermineScanID(cs)
if error == True or cs.scanID == lit.stUnknown:
raise ValueError("{} ERROR! Cannot determine MR Scan ID".format(
logTag()))
## 1. Run tests
setname = cs.scanID
piqttests = []
if setname == 'QA1':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA1_Uniformity", "M", 3, 1, 30),
("QA1_Uniformity", "M", 3, 2, 100),
("QA1_Linearity", "M", 2, 1, 30),
("QA1_SliceProfile", "M", 4, 1, 30),
("QA1_SliceProfile", "M", 4, 2, 100),
("QA1_MTF", "M", 5, 1, 30),
("QA1_MTF", "M", 5, 2, 100),
]
elif setname == 'QA2':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA2_Uniformity", "M", 2, 1, 15),
("QA2_SliceProfile", "M", 3, 1, 15),
]
elif setname == 'QA3':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA3_Uniformity", "M", 1, 1, 50),
("QA3_Uniformity", "M", 1, 2, 100),
("QA3_Uniformity", "M", 1, 3, 150),
]
reportkeyvals = []
for piqt in piqttests:
cs = QCMR_lib.PiQT_Struct(dcmInfile, pixeldataIn, dicomMode, piqt)
cs.verbose = None
## 1b. Run tests
sliceno = qclib.ImageSliceNumber(cs, piqt)
if sliceno < 0:
print(logTag() + "[mrheader]: ", piqt,
"not available for given image")
sys.exit()
dicominfo = qclib.DICOMInfo(cs, info, sliceno)
if len(dicominfo) > 0:
idname = "_" + setname + make_idname(qclib, cs, sliceno)
for di in dicominfo:
reportkeyvals.append((di[0] + idname, str(di[1])))
## 2. Build xml output
# plugionversion is newly added in for this plugin since pywad2
results.addChar('pluginversion' + idname, str(
qclib.qcversion)) # do not specify level, use default from config
for key, val in reportkeyvals:
val2 = "".join([x if ord(x) < 128 else '?'
for x in val]) #ignore non-ascii
results.addChar(key,
str(val2)[:min(len(str(val)), 128)]
) # do not specify level, use default from config
def mammoqc_series(data, results, **kwargs):
"""
QCMammo_UMCU checks:
Uniformity (5 rois) and SNR (hologic),
DoseRatio (empirical/calculated from DICOM)
Artefacts (spots, dead pixels)
Workflow:
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
inputfile = data.series_filelist[0] # give me a filename
## 2. Check data format
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag())
## 3. Build and populate qcstructure
remark = ""
qcmammolib = QCMammo_lib.Mammo_QC()
cs_mam = QCMammo_lib.MammoStruct(dcmInfile, pixeldataIn)
cs_mam.verbose = False # do not produce detailed logging
if qcmammolib.NeedsCropping(cs_mam):
cs_mam.expertmode = True
qcmammolib.RestrictROI(cs_mam)
remark = "CROPPED"
## 4. Run tests
# Uniformity check
error = qcmammolib.Uniformity(cs_mam)
if error:
remark += "/ERROR_UNIFORMITY"
# Contrast L50
error = qcmammolib.L50Contrast(cs_mam) # doesn't do anything if not L50
if error:
remark += "/ERROR_L50CONTRAST"
# Dose Ratio
error = qcmammolib.DoseRatio(cs_mam)
if error:
remark += "/ERROR_DOSERATIO"
# Artefacts
error = qcmammolib.Artefacts(cs_mam)
if error:
remark += "/ERROR_ARTEFACTS"
## 5. Build xml output
## Struct now contains all the results and we can write these to the
## WAD IQ database
includedlist = [
'unif_pct', 'snr_hol', 'doseratio', 'art_clusters',
'expert_inoutoverin', 'contrast_snr'
]
excludedlist = [
'verbose', 'dcmInfile', 'pixeldataIn', 'hasmadeplots', 'means',
'stdevs', 'unif', 'snr_hol', 'unif_rois', 'doseratio', 'art_clusters',
'art_image', 'art_borderpx', 'art_threshold', 'art_rois', 'expertmode',
'expert_roipts', 'expert_frac', 'expert_inoutoverin', 'filtername',
'scannername', 'contrast_rois', 'contrast_mean', 'contrast_sd'
]
idname = '_' + cs_mam.filtername
if "SUMPRES" in idname:
idname = "" # only one image
results.addChar('NOTE' + idname, remark)
for elem in cs_mam.__dict__:
if elem in includedlist:
newkeys = []
newvals = []
try:
elemval = cs_mam.__dict__[elem]
if 'contrast_snr' in elem: # array
for ix, snr in enumerate(elemval):
newkeys.append('CNR' + str(ix))
newvals.append(snr)
elif 'art_clusters' in elem:
newkeys.append(str(elem))
newvals.append(len(elemval))
else:
newkeys.append(str(elem))
newvals.append(elemval)
except:
print(logTag() + "error for", elem)
tmpdict = {}
for key, val in zip(newkeys, newvals):
results.addFloat(key + str(idname), val, quantity=str(key))
## 6. Build artefact picture thumbnail
filename = 'test' + idname + '.jpg' # Use jpg if a thumbnail is desired
#object_naam_pad = outputfile.replace('result.xml','test'+idname+'.jpg') # Use jpg if a thumbnail is desired
qcmammolib.saveAnnotatedArtefactImage(cs_mam, filename)
results.addObject('ArtefactImage' + idname, filename)
def ctqc_series(data, results, params):
"""
QCCT_UMCU Checks: extension of Philips QuickIQ (also for older scanners without that option), for both Head and Body if provided
Uniformity
HU values
Noise
Linearity
Workflow:
1. Read image or sequence
2. Run test
3. Build xml output
"""
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=False, logTag=logTag())
qclib = QCCT_lib.CT_QC()
cs = QCCT_lib.CTStruct(dcmInfile=dcmInfile,
pixeldataIn=pixeldataIn,
dicomMode=dicomMode)
cs.forceScanner = _getScannerDefinition(params)
cs.verbose = False
## id scanner
error = qclib.DetermineCTID(cs)
if (error == True or cs.guessScanner.name == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine CT ID".format(logTag))
error = qclib.HeadOrBody(cs)
if (error == True or cs.anatomy == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine Anatomy".format(logTag))
idname = ""
if cs.anatomy == lit.stHead:
idname = "_H"
else:
idname = "_B"
# only uncomment if same config used for all scanners: idname += cs.guessScanner.name
## 2. Run tests
error = qclib.AnalyseCT(cs)
if error:
raise ValueError("{} ERROR! Error in AnalyseCT".format(logTag))
## Struct now contains all the results and we can write these to the
## WAD IQ database
includedlist = [
'roiavg',
'roisd',
'snr_hol',
'unif',
'linearity',
'maxdev',
'shiftxypx',
]
excludedlist = [
'verbose', 'dcmInfile', 'pixeldataIn', 'dicomMode', 'hasmadeplots',
'guessScanner', 'anatomy', 'roiavg', 'roisd', 'snr_hol', 'unif',
'linearity', 'maxdev', 'shiftxypx', 'valid'
'skull_avg', 'unif_slice', 'unif_rois'
]
for elem in cs.__dict__:
if elem in includedlist:
newkeys = []
newvals = []
try:
elemval = cs.__dict__[elem]
if 'roiavg' in elem: # array of avgs
newkeys.append('MeanCenter')
newvals.append(elemval[0])
newkeys.append('MeanAir')
newvals.append(elemval[3])
elif 'shiftxypx' in elem:
newkeys.append('shiftxpx')
newvals.append(elemval[0])
newkeys.append('shiftypx')
newvals.append(elemval[1])
else:
newkeys.append(str(elem))
newvals.append(elemval)
except:
print logTag() + "error for", elem
elemval = -1.
for key, val in zip(newkeys, newvals):
results.addFloat(key + str(idname), val, quantity=str(key))
## Build thumbnail
filename = 'test' + idname + '.jpg' # Use jpg if a thumbnail is desired
if cs.dicomMode == wadwrapper_lib.stMode2D:
scipy.misc.imsave(filename, cs.pixeldataIn.transpose(
)) # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
else:
scipy.misc.imsave(filename, (cs.pixeldataIn[cs.unif_slice]).transpose(
)) # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
results.addObject('CTslice' + idname, filename)
def mrheader_series(data,results,**kwargs):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
info = 'dicom'
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=True,logTag=logTag())
qclib = QCMR_lib.PiQT_QC()
cs = QCMR_lib.PiQT_Struct(dcmInfile=dcmInfile,pixeldataIn=pixeldataIn,dicomMode=dicomMode,piqttest=None)
cs.verbose = False
## id scanner
idname = ""
error = qclib.DetermineScanID(cs)
if error == True or cs.scanID == lit.stUnknown:
raise ValueError("{} ERROR! Cannot determine MR Scan ID".format(logTag))
## 1. Run tests
setname = cs.scanID
piqttests = []
if setname == 'QA1':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA1_Uniformity", "M",3,1, 30),
("QA1_Uniformity", "M",3,2,100),
("QA1_Linearity" , "M",2,1, 30),
("QA1_SliceProfile", "M",4,1, 30),
("QA1_SliceProfile", "M",4,2,100),
("QA1_MTF", "M",5,1, 30),
("QA1_MTF", "M",5,2,100),
]
elif setname== 'QA2':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA2_Uniformity", "M",2,1, 15),
("QA2_SliceProfile", "M",3,1, 15),
]
elif setname == 'QA3':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA3_Uniformity", "M",1,1, 50),
("QA3_Uniformity", "M",1,2,100),
("QA3_Uniformity", "M",1,3,150),
]
reportkeyvals = []
for piqt in piqttests:
cs = QCMR_lib.PiQT_Struct(dcmInfile,pixeldataIn,dicomMode,piqt)
cs.verbose = None
## 1b. Run tests
sliceno = qclib.ImageSliceNumber(cs,piqt)
if sliceno <0:
print logTag()+"[mrheader]: ", piqt, "not available for given image"
sys.exit()
dicominfo = qclib.DICOMInfo(cs,info,sliceno)
if len(dicominfo) >0:
idname = "_"+setname+make_idname(qclib,cs,sliceno)
for di in dicominfo:
reportkeyvals.append( (di[0]+idname,str(di[1])) )
## 2. Build xml output
# plugionversion is newly added in for this plugin since pywad2
results.addChar('pluginversion'+idname, str(qclib.qcversion)) # do not specify level, use default from config
for key,val in reportkeyvals:
val2 = "".join([x if ord(x) < 128 else '?' for x in val]) #ignore non-ascii
results.addChar(key, str(val2)[:min(len(str(val)),128)]) # do not specify level, use default from config
def mrqc_series(data, results, **kwargs):
"""
QCMR_UMCU Checks: Philips PiQT reimplementen in python
Uniformity (several ways)
Geometrical deformation
ArtifactLevel
Signal-to-noise (several positions)
Resolution (MTF, FTW, SliceWidth)
Workflow:
1. Read image or sequence
2. Run test
3. Build xml output
"""
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
data.series_filelist[0], headers_only=False, logTag=logTag())
qclib = QCMR_lib.PiQT_QC()
cs = QCMR_lib.PiQT_Struct(dcmInfile=dcmInfile,
pixeldataIn=pixeldataIn,
dicomMode=dicomMode,
piqttest=None)
cs.verbose = False
## id scanner
idname = ""
error = qclib.DetermineScanID(cs)
if error == True or cs.scanID == lit.stUnknown:
raise ValueError("{} ERROR! Cannot determine MR Scan ID".format(
logTag()))
## 2. Run tests
setname = cs.scanID
piqttests = []
if setname == 'QA1':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA1_Uniformity", "M", 3, 1, 30),
("QA1_Uniformity", "M", 3, 2, 100),
("QA1_Linearity", "M", 2, 1, 30),
("QA1_SliceProfile", "M", 4, 1, 30),
("QA1_SliceProfile", "M", 4, 2, 100),
("QA1_MTF", "M", 5, 1, 30),
("QA1_MTF", "M", 5, 2, 100),
]
elif setname == 'QA2':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA2_Uniformity", "M", 2, 1, 15),
("QA2_SliceProfile", "M", 3, 1, 15),
]
elif setname == 'QA3':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA3_Uniformity", "M", 1, 1, 50),
("QA3_Uniformity", "M", 1, 2, 100),
("QA3_Uniformity", "M", 1, 3, 150),
]
reportkeyvals = []
for piqt in piqttests:
print("[mrqc]", 2, piqt)
if "Uniformity" in piqt[0]:
test = lit.stTestUniformity
doTest = "SNR_ArtifactLevel_FloodFieldUniformity"
if "Linearity" in piqt[0]:
test = lit.stTestSpatialLinearity
doTest = "SpatialLinearity"
if "SliceProfile" in piqt[0]:
test = lit.stTestSliceProfile
doTest = "SliceProfile"
if "MTF" in piqt[0]:
test = lit.stTestMTF
doTest = "MTF"
cs = QCMR_lib.PiQT_Struct(dcmInfile, pixeldataIn, dicomMode, piqt)
cs.verbose = None
if "FloodFieldUniformity" in doTest: # FFU also contains SNR and ArtifactLevel
error = qclib.FloodFieldUniformity(cs)
if not error:
import numpy as np
idname = "_" + setname + make_idname(qclib, cs, cs.snr_slice)
reportkeyvals.append(("S/N (B)" + idname, cs.snr_SNB))
reportkeyvals.append(
("Art_Level" + idname, cs.artefact_ArtLevel))
reportkeyvals.append(("T/C-20" + idname, cs.ffu_TCm20))
reportkeyvals.append(("C-20/C-10" + idname, cs.ffu_Cm20Cm10))
reportkeyvals.append(("C-10/C+10" + idname, cs.ffu_Cm10Cp10))
reportkeyvals.append(("C+10/C+20" + idname, cs.ffu_Cp10Cp20))
reportkeyvals.append(("C+20/Max" + idname, cs.ffu_Cp20MAX))
reportkeyvals.append(("Rad 10%" + idname, cs.ffu_rad10))
reportkeyvals.append(("Int_Unif" + idname, cs.ffu_lin_unif))
## Build thumbnail
filename = 'FFU' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveResultImage(cs, 'FFU', filename)
results.addObject('FFU' + '_' + idname, filename)
elif "ArtifactLevel" in doTest: # Artifact also contains SNR
error = qclib.ArtifactLevel(cs)
if not error:
idname = "_" + setname + make_idname(qclib, cs, cs.snr_slice)
reportkeyvals.append(("S/N (B)" + idname, cs.snr_SNB))
reportkeyvals.append(
("Art_Level" + idname, cs.artefact_ArtLevel))
elif "SNR" in doTest:
error = qclib.SNR(cs)
if not error:
idname = "_" + setname + make_idname(qclib, cs, cs.snr_slice)
reportkeyvals.append(("S/N (B)" + idname, cs.snr_SNB))
if "SpatialLinearity" in doTest:
error = qclib.SpatialLinearity(cs)
if not error:
idname = "_" + setname + make_idname(qclib, cs, cs.lin_slice)
reportkeyvals.append(
("phant_rot" + idname, cs.lin_phantomrotdeg))
reportkeyvals.append(("m/p_angle" + idname, str(-360)))
reportkeyvals.append(("size_hor" + idname, cs.lin_sizehor))
reportkeyvals.append(("size_ver" + idname, cs.lin_sizever))
reportkeyvals.append(
("hor_int_av" + idname, cs.lin_intshiftavg[0]))
reportkeyvals.append(
("hor_int_dev" + idname, cs.lin_intshiftsdev[0]))
reportkeyvals.append(
("hor_max_right" + idname, cs.lin_shiftmax[0]))
reportkeyvals.append(
("hor_max_left" + idname, cs.lin_shiftmin[0]))
reportkeyvals.append(
("hor_diff_av" + idname, cs.lin_intdiffavg[0]))
reportkeyvals.append(
("hor_diff_dev" + idname, cs.lin_intdiffsdev[0]))
reportkeyvals.append(
("hor_max" + idname, cs.lin_intdiffmax[0]))
reportkeyvals.append(
("hor_min" + idname, cs.lin_intdiffmin[0]))
reportkeyvals.append(
("ver_int_av" + idname, cs.lin_intshiftavg[1]))
reportkeyvals.append(
("ver_int_dev" + idname, cs.lin_intshiftsdev[1]))
reportkeyvals.append(
("ver_max_up" + idname, cs.lin_shiftmax[1]))
reportkeyvals.append(
("ver_max_down" + idname, cs.lin_shiftmin[1]))
reportkeyvals.append(
("ver_diff_av" + idname, cs.lin_intdiffavg[1]))
reportkeyvals.append(
("ver_diff_dev" + idname, cs.lin_intdiffsdev[1]))
reportkeyvals.append(
("ver_max" + idname, cs.lin_intdiffmax[1]))
reportkeyvals.append(
("ver_min" + idname, cs.lin_intdiffmin[1]))
## Build thumbnail
filename = 'LIN' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveResultImage(cs, 'LIN', filename)
results.addObject('LIN' + '_' + idname, filename)
if "SliceProfile" in doTest:
error = qclib.SliceProfile(cs)
if not error:
idname = "_" + setname + make_idname(qclib, cs, cs.sp_slice)
reportkeyvals.append(
("Pos_shift" + idname, cs.sp_phantomshift))
reportkeyvals.append(("FWHM" + idname, cs.sp_slicewidth_fwhm))
reportkeyvals.append(("FWTM" + idname, cs.sp_slicewidth_fwtm))
reportkeyvals.append(
("Slice_int" + idname, cs.sp_slicewidth_lineint))
reportkeyvals.append(
("Angle" + idname, cs.sp_phantomzangledeg))
reportkeyvals.append(
("phant_rot" + idname, cs.sp_phantomrotdeg))
reportkeyvals.append(
("Phase_Shift" + idname, cs.sp_phaseshift))
## Build thumbnail
filename = 'SLP' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveResultImage(cs, 'SLP', filename)
results.addObject('SLP' + '_' + idname, filename)
if "MTF" in doTest:
error = qclib.MTF(cs)
if not error:
idname = "_" + setname + make_idname(qclib, cs, cs.mtf_slice)
reportkeyvals.append(
("Hor_pxl_size" + idname, cs.mtf_pixelsize[0]))
reportkeyvals.append(
("Ver_pxl_size" + idname, cs.mtf_pixelsize[1]))
## Build thumbnail
filename = 'MTF' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveResultImage(cs, 'MTF', filename)
results.addObject('MTF' + '_' + idname, filename)
if error:
raise ValueError("{} ERROR! processing error in {} {}".format(
logTag(), piqt, doTest))
for key, val in reportkeyvals:
results.addFloat(key, val, quantity=str(key.split('_QA')[0]))
def mrqc_series(data,results,**kwargs):
"""
QCMR_UMCU Checks: Philips PiQT reimplementen in python
Uniformity (several ways)
Geometrical deformation
ArtifactLevel
Signal-to-noise (several positions)
Resolution (MTF, FTW, SliceWidth)
Workflow:
1. Read image or sequence
2. Run test
3. Build xml output
"""
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],headers_only=False,logTag=logTag())
qclib = QCMR_lib.PiQT_QC()
cs = QCMR_lib.PiQT_Struct(dcmInfile=dcmInfile,pixeldataIn=pixeldataIn,dicomMode=dicomMode,piqttest=None)
cs.verbose = False
## id scanner
idname = ""
error = qclib.DetermineScanID(cs)
if error == True or cs.scanID == lit.stUnknown:
raise ValueError("{} ERROR! Cannot determine MR Scan ID".format(logTag))
## 2. Run tests
setname = cs.scanID
piqttests = []
if setname == 'QA1':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA1_Uniformity", "M",3,1, 30),
("QA1_Uniformity", "M",3,2,100),
("QA1_Linearity" , "M",2,1, 30),
("QA1_SliceProfile", "M",4,1, 30),
("QA1_SliceProfile", "M",4,2,100),
("QA1_MTF", "M",5,1, 30),
("QA1_MTF", "M",5,2,100),
]
elif setname== 'QA2':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA2_Uniformity", "M",2,1, 15),
("QA2_SliceProfile", "M",3,1, 15),
]
elif setname == 'QA3':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("QA3_Uniformity", "M",1,1, 50),
("QA3_Uniformity", "M",1,2,100),
("QA3_Uniformity", "M",1,3,150),
]
reportkeyvals = []
for piqt in piqttests:
print "[mrqc]",2,piqt
if "Uniformity" in piqt[0]:
test = lit.stTestUniformity
doTest = "SNR_ArtifactLevel_FloodFieldUniformity"
if "Linearity" in piqt[0]:
test = lit.stTestSpatialLinearity
doTest = "SpatialLinearity"
if "SliceProfile" in piqt[0]:
test = lit.stTestSliceProfile
doTest = "SliceProfile"
if "MTF" in piqt[0]:
test = lit.stTestMTF
doTest = "MTF"
cs = QCMR_lib.PiQT_Struct(dcmInfile,pixeldataIn,dicomMode,piqt)
cs.verbose = None
if "SNR" in doTest:
error = qclib.SNR(cs)
if not error:
idname = "_"+setname+make_idname(qclib,cs,cs.snr_slice)
reportkeyvals.append( ("S/N (B)"+idname,cs.snr_SNB) )
if "ArtifactLevel" in doTest:
error = qclib.ArtifactLevel(cs)
if not error:
idname = "_"+setname+make_idname(qclib,cs,cs.snr_slice)
reportkeyvals.append( ("Art_Level"+idname,cs.artefact_ArtLevel) )
if "FloodFieldUniformity" in doTest:
error = qclib.FloodFieldUniformity(cs)
if not error:
import numpy as np
idname = "_"+setname+make_idname(qclib,cs,cs.snr_slice)
reportkeyvals.append( ("T/C-20"+idname,cs.ffu_TCm20) )
reportkeyvals.append( ("C-20/C-10"+idname,cs.ffu_Cm20Cm10) )
reportkeyvals.append( ("C-10/C+10"+idname,cs.ffu_Cm10Cp10) )
reportkeyvals.append( ("C+10/C+20"+idname,cs.ffu_Cp10Cp20) )
reportkeyvals.append( ("C+20/Max"+idname,cs.ffu_Cp20MAX) )
reportkeyvals.append( ("Rad 10%"+idname,cs.ffu_rad10) )
reportkeyvals.append( ("Int_Unif"+idname,cs.ffu_lin_unif) )
## Build thumbnail
filename = 'test'+idname+'.jpg' # Use jpg if a thumbnail is desired
scipy.misc.imsave(filename,cs.lastimage.transpose()) # MODULE EXPECTS PYQTGRAPH DATA: X AND Y ARE TRANSPOSED!
results.addObject('FFU'+'_'+idname,filename)
if "SpatialLinearity" in doTest:
error = qclib.SpatialLinearity(cs)
if not error:
idname = "_"+setname+make_idname(qclib,cs,cs.lin_slice)
reportkeyvals.append( ("phant_rot"+idname,cs.lin_phantomrotdeg) )
reportkeyvals.append( ("m/p_angle"+idname,str(-360)) )
reportkeyvals.append( ("size_hor"+idname,cs.lin_sizehor) )
reportkeyvals.append( ("size_ver"+idname,cs.lin_sizever) )
reportkeyvals.append( ("hor_int_av"+idname,cs.lin_intshiftavg[0]) )
reportkeyvals.append( ("hor_int_dev"+idname,cs.lin_intshiftsdev[0]) )
reportkeyvals.append( ("hor_max_right"+idname,cs.lin_shiftmax[0]) )
reportkeyvals.append( ("hor_max_left"+idname,cs.lin_shiftmin[0]) )
reportkeyvals.append( ("hor_diff_av"+idname,cs.lin_intdiffavg[0]) )
reportkeyvals.append( ("hor_diff_dev"+idname,cs.lin_intdiffsdev[0]) )
reportkeyvals.append( ("hor_max"+idname,cs.lin_intdiffmax[0]) )
reportkeyvals.append( ("hor_min"+idname,cs.lin_intdiffmin[0]) )
reportkeyvals.append( ("ver_int_av"+idname,cs.lin_intshiftavg[1]) )
reportkeyvals.append( ("ver_int_dev"+idname,cs.lin_intshiftsdev[1]) )
reportkeyvals.append( ("ver_max_up"+idname,cs.lin_shiftmax[1]) )
reportkeyvals.append( ("ver_max_down"+idname,cs.lin_shiftmin[1]) )
reportkeyvals.append( ("ver_diff_av"+idname,cs.lin_intdiffavg[1]) )
reportkeyvals.append( ("ver_diff_dev"+idname,cs.lin_intdiffsdev[1]) )
reportkeyvals.append( ("ver_max"+idname,cs.lin_intdiffmax[1]) )
reportkeyvals.append( ("ver_min"+idname,cs.lin_intdiffmin[1]) )
if "SliceProfile" in doTest:
error = qclib.SliceProfile(cs)
if not error:
idname = "_"+setname+make_idname(qclib,cs,cs.sp_slice)
reportkeyvals.append( ("Pos_shift"+idname,cs.sp_phantomshift) )
reportkeyvals.append( ("FWHM"+idname,cs.sp_slicewidth_fwhm) )
reportkeyvals.append( ("FWTM"+idname,cs.sp_slicewidth_fwtm) )
reportkeyvals.append( ("Slice_int"+idname,cs.sp_slicewidth_lineint) )
reportkeyvals.append( ("Angle"+idname,cs.sp_phantomzangledeg) )
reportkeyvals.append( ("phant_rot"+idname,cs.sp_phantomrotdeg) )
reportkeyvals.append( ("Phase_Shift"+idname,cs.sp_phaseshift) )
if "MTF" in doTest:
error = qclib.MTF(cs)
if not error:
idname = "_"+setname+make_idname(qclib,cs,cs.mtf_slice)
reportkeyvals.append( ("Hor_pxl_size"+idname,cs.mtf_pixelsize[0]) )
reportkeyvals.append( ("Ver_pxl_size"+idname,cs.mtf_pixelsize[1]) )
if error:
raise ValueError("{} ERROR! processing error in {} {}".format(logTag,piqt,doTest))
for key,val in reportkeyvals:
results.addFloat(key, val, quantity=str(key.split('_QA')[0]))