def header_series(data, results, action):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build results output
"""
try:
params = action['params']
except KeyError:
params = {}
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput([data.series_filelist[0][0]], headers_only=True, logTag=logTag())
cs = qc_lib.fBIRN_Struct(dcmInfile=dcmInfile, pixeldataIn=pixeldataIn, dicomMode=dicomMode)
cs.verbose = False
## 1. run tests
reportkeyvals = []
dicominfo = qc_info.DICOMInfo(cs, 'dicom', 0)
if len(dicominfo) >0:
for di in dicominfo:
reportkeyvals.append( (di[0],str(di[1])) )
## 2. Build xml/json output
varname = 'pluginversion'
results.addString(varname, str(qc_lib.__version__))
for key,val in reportkeyvals:
val2 = "".join([x if ord(x) < 128 else '?' for x in val]) #ignore non-ascii
results.addString(key, str(val2)[:min(len(str(val)),100)])
def header_series(data, results, action, idname=None):
"""
Read selected dicomfields and write to IQC database
"""
try:
params = action['params']
except KeyError:
params = {}
inputfile = data.series_filelist[0] # give me a [filename]
wrapper_params = [
'rgbchannel',
'auto_suffix',
] # parameters for wrapper only
rgbchannel = params.get('rgbchannel', 'B')
dcmInfile, pixelData, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=True, logTag=logTag(), rgbchannel=rgbchannel)
qc = QCUS2_lib.Analysis(dcmInfile, pixelData)
for name, value in params.items():
if not name in wrapper_params:
qc.set_param(name, value)
# find probename
idname = ''
if params.get('auto_suffix', False):
if idname is None:
idname = '_' + qc.imageID(probeonly=True)
# add pluginversion to 'result' object
add_plugin_version(qc, results, 'pluginversion' + idname)
# run tests
dicominfo = qc.dicom_info()
# add results to 'result' object
for dtype in dicominfo.keys():
for key, val in dicominfo[dtype]:
if dtype in ['int', 'float']:
results.addFloat(key + idname, val)
elif dtype in ['string']:
results.addString(key + idname,
str(val)[:min(len(str(val)), 100)])
elif dtype in ['bool']:
results.addBool(key + idname, val)
elif dtype in ['object']:
results.addObject(key + idname, val)
else:
raise ValueError(
"Result '{}' has unknown result type '{}'".format(
key, dtype))
def OCR(data, results, action):
"""
Use pyOCR which for OCR
"""
try:
params = action['params']
except KeyError:
params = {}
inputfile = data.series_filelist[0] # give me a [filename]
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag())
# solve ocr params
regions = {}
for k, v in params.items():
#'OCR_TissueIndex:xywh' = 'x;y;w;h'
#'OCR_TissueIndex:prefix' = 'prefix'
#'OCR_TissueIndex:suffix' = 'suffix'
if k.startswith('OCR_'):
split = k.find(':')
name = k[:split]
stuff = k[split + 1:]
if not name in regions:
regions[name] = {'prefix': '', 'suffix': ''}
if stuff == 'xywh':
regions[name]['xywh'] = [int(p) for p in v.split(';')]
elif stuff == 'prefix':
regions[name]['prefix'] = v
elif stuff == 'suffix':
regions[name]['suffix'] = v
elif stuff == 'type':
regions[name]['type'] = v
for name, region in regions.items():
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:
value = ocr_lib.txt2type(txt, region['type'], region['prefix'],
region['suffix'])
if region['type'] == 'float':
results.addFloat(name, value)
elif region['type'] == 'string':
results.addString(name, value)
elif region['type'] == 'bool':
results.addBool(name, value)
def qc_series(data, results, action):
"""
QCMR_UMCU Checks: Philips fBIRN analysis reimplemented in python
Weisskoff analysis
Ghosting
Residual Noise
Temporal Fluctuation
Spatial Noise
Workflow:
1. Read image or sequence
2. Run test
3. Build results output
"""
try:
params = action['params']
except KeyError:
params = {}
## 1. read images
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],
headers_only=False, logTag=logTag(),
skip_check=True, splitOnPosition=False)
qclib = qc_lib.fBIRN_QC()
cs = qc_lib.fBIRN_Struct(dcmInfile=dcmInfile, pixeldataIn=pixeldataIn, dicomMode=dicomMode)
cs.verbose = True # output lot's of comments
## 2. Run tests
reportkeyvals = []
error, namevals = qclib.QC(cs)
if not error:
for typ, name, val in namevals:
reportkeyvals.append( (typ, name, val) )
if error:
raise ValueError("{} ERROR! processing error in QC".format(logTag()))
for typ, name, val in reportkeyvals:
if typ == 'float':
results.addFloat(name, val)
elif typ == 'string':
results.addString(name, val)
elif typ == 'object':
results.addObject(name, val)
def snr_series(data, results, action):
"""
QCMR_UMCU Checks:
B0 mapping test
Workflow:
1. Read image or sequence
2. Run test
3. Build results output
"""
try:
params = action['params']
except KeyError:
params = {}
## 1. read images
dcmInfile,pixeldataIn,dicomMode = wadwrapper_lib.prepareInput(data.series_filelist[0],
headers_only=False, logTag=logTag(),
skip_check=True, splitOnPosition=False)
qclib = qc_lib.fBIRN_QC()
cs = qc_lib.fBIRN_Struct(dcmInfile=dcmInfile, pixeldataIn=pixeldataIn, dicomMode=dicomMode)
cs.verbose = True # output lot's of comments
if 'circleradiusfactor' in params:
qclib.usePartCircle = float(params['circleradiusfactor'])
## 2. Run tests
reportkeyvals = []
error, namevals = qclib.PureSNR(cs)
if not error:
for typ, name, val in namevals:
reportkeyvals.append( (typ, name, val) )
if error:
raise ValueError("{} ERROR! processing error in PureSNR".format(logTag()))
for typ, name, val in reportkeyvals:
if typ == 'float':
results.addFloat(name, val)
elif typ == 'string':
results.addString(name, val)
elif typ == 'object':
results.addObject(name, val)
def header_series(data, results, action):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
try:
params = action['params']
except KeyError:
params = {}
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
override_settings(cs, params)
error = qcctlib.HeadOrBody(cs)
if(error == True or cs.anatomy == lit.stUnknown):
raise ValueError("{} ERROR! Cannot determine Anatomy".format(logTag))
result_dict = {}
# 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
varname = 'pluginversion'
results.addString(varname, str(qcctlib.qcversion))
varname = 'Anatomy'
results.addString(varname, str(cs.anatomy))
for di in dicominfo:
varname = di[0]
results.addString(varname, str(di[1])[:min(len(str(di[1])),100)])
def qc_series(data, results, action):
"""
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
"""
try:
params = action['params']
except KeyError:
params = {}
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),
]
elif setname == 'MRLSNR':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, element,
("MRL_SNR", "M", 1, 1, 0),
("MRL_1_SNR", "M", 1, 1, 1),
("MRL_2_SNR", "M", 1, 1, 2),
("MRL_3_SNR", "M", 1, 1, 3),
("MRL_4_SNR", "M", 1, 1, 4),
("MRL_5_SNR", "M", 1, 1, 5),
("MRL_6_SNR", "M", 1, 1, 6),
("MRL_7_SNR", "M", 1, 1, 7),
("MRL_8_SNR", "M", 1, 1, 8),
]
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"
if "SNR" in piqt[0]:
# MRL SNR test is performed per slice. Prepare input for single dicom file
test = lit.stTestSNR
doTest = "SNR"
dcmsnr = [data.series_filelist[0][piqt[4]]]
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
dcmsnr, headers_only=False, logTag=logTag())
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)
varname = 'FFU' + '_' + idname
results.addObject(varname, 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:
# MRL SNR test only needs S/N (B) as output/specd value
error = qclib.SNR(cs)
if not error:
idname = "_" + setname + make_idname(
qclib, cs, cs.snr_slice) + "_" + str(piqt[4])
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]))
reportkeyvals.append(("lin_NEMA" + idname, cs.lin_nema_max))
## Build thumbnail
filename = 'LIN' + idname + '.jpg' # Use jpg if a thumbnail is desired
qclib.saveResultImage(cs, 'LIN', filename)
varname = 'LIN' + '_' + idname
results.addObject(varname, 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)
varname = 'SLP' + '_' + idname
results.addObject(varname, 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)
varname = 'MTF' + '_' + idname
results.addObject(varname, filename)
if error:
raise ValueError("{} ERROR! processing error in {} {}".format(
logTag(), piqt, doTest))
for key, val in reportkeyvals:
results.addFloat(key, val)
def header_series(data, results, action):
"""
Read selected dicomfields and write to IQC database
Workflow:
1. Run tests
2. Build xml output
"""
try:
params = action['params']
except KeyError:
params = {}
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),
]
elif setname == 'MRLSNR':
piqttests = [ # seq test, "M", philips_slicenumber, echonumber, echotime,
("MRL_SNR", "M", 1, 1, 0),
("MRL_1_SNR", "M", 1, 1, 1),
("MRL_2_SNR", "M", 1, 1, 2),
("MRL_3_SNR", "M", 1, 1, 3),
("MRL_4_SNR", "M", 1, 1, 4),
("MRL_5_SNR", "M", 1, 1, 5),
("MRL_6_SNR", "M", 1, 1, 6),
("MRL_7_SNR", "M", 1, 1, 7),
("MRL_8_SNR", "M", 1, 1, 8),
]
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:
msg = "{} [mrheader]: {} not available for given image".format(
logTag(), piqt)
print(msg)
raise ValueError(msg)
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
floatlist = ['Central_freq']
# plugionversion is newly added in for this plugin since pywad2
varname = 'pluginversion' + idname
results.addString(varname,
str(qclib.qcversion)) # do use default from config
for key, val in reportkeyvals:
is_float = False
for fl in floatlist:
if key.startswith(fl):
is_float = True
break
if is_float:
try:
val2 = float(val)
except ValueError:
val2 = -1
results.addFloat(key, val2)
else:
val2 = "".join([x if ord(x) < 128 else '?'
for x in val]) #ignore non-ascii
results.addString(
key,
str(val2)
[:min(len(str(val)), 100)]) # do use default from config
def qc_series(data, results, action):
"""
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
"""
try:
params = action['params']
except KeyError:
params = {}
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
override_settings(cs, params)
## 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))
# 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 = [
'skull_avg',
'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'
'unif_slice',
'unif_rois'
]
skull_val = -2024 # low value, will need a higher
# make sure skull_avg is used if valid, but preserve order of results
for elem in cs.__dict__:
if elem in includedlist:
try:
elemval = cs.__dict__[elem]
if 'skull_avg' in elem: # skull_avg only defined for head
skull_val = elemval
break
except:
print(logTag()+"error for", elem)
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])
if skull_val <= -1024: # skull_avg only defined for head; if not head, then take teflon plug
newkeys.append('MeanHigh')
newvals.append(max(elemval))
elif 'shiftxypx' in elem:
newkeys.append('shiftxpx')
newvals.append(elemval[0])
newkeys.append('shiftypx')
newvals.append(elemval[1])
elif 'skull_avg' in elem:
skull_val = elemval
if elemval > -1024: # skull_avg only defined for head; if not head, then take teflon plug
newkeys.append('MeanHigh')
newvals.append(elemval)
else:
newkeys.append(str(elem))
newvals.append(elemval)
except:
print(logTag()+"error for",elem)
elemval = -1.
for key,val in zip(newkeys,newvals):
varname = key
results.addFloat(varname, val)
## Build thumbnail
filename = 'test'+'.jpg' # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename)
varname = 'CTslice'
results.addObject(varname, filename)
def setup_series(inputfile, params, headers_only, for_action):
"""
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
rgbchannel = params.get('rgbchannel', 'B')
dcmInfile, pixeldataIn, dicomMode = wadwrapper_lib.prepareInput(
inputfile,
headers_only=headers_only,
logTag=logTag(),
rgbchannel=rgbchannel)
# 3. Build and populate qcstructure
qclib = QCUS_lib.US_QC(guimode=False)
cs = QCUS_lib.USStruct(dcmInfile, pixeldataIn, dicomMode)
if for_action == 'ocr':
optional_pars = [ # parname, attribname, type, default
('verbose', 'verbose', 'boolean',
False), # by default do not produce detailed logging
('auto_suffix', 'auto_suffix', 'boolean',
True), # by default try to add a probename suffix to each result
# ocr_threshold and ocr_zoom handled in OCR action
]
required_pars = []
elif for_action == 'qc':
optional_pars = [ # parname, attribname, type, default
('verbose', 'verbose', 'boolean',
False), # by default do not produce detailed logging
('auto_suffix', 'auto_suffix', 'boolean',
True), # by default try to add a probename suffix to each result
('signal_thresh', 'signal_thresh', 'int',
None), # no default value
('cluster_mode', 'cluster_mode', 'string',
None), # no default value
('uni_start', 'uni_start', 'string', None), # no default value
('rev_bbox', 'rev_forcebbox', 'stringint4',
None), # no default value
('uni_range_model', 'uni_range_model', 'string',
None), # no default value
]
required_pars = [ # parname, attribname, type
('uni_filter', 'uni_filter', 'int'),
('uni_delta', 'uni_delta', 'float'),
('uni_depth', 'uni_depth', 'float'),
('sen_filter', 'sen_filter', 'int'),
('sen_delta', 'sen_delta', 'float'),
('ver_offset', 'ver_offset', 'int'),
('hor_offset', 'hor_offset', 'int'),
('fitcircle_frac', 'fitcircle_frac', 'float'),
('cluster_fminsize', 'cluster_fminsize', 'float'),
]
elif for_action == 'hdrs':
optional_pars = [ # parname, attribname, type, default
('verbose', 'verbose', 'boolean',
False), # by default do not produce detailed logging
('auto_suffix', 'auto_suffix', 'boolean',
True), # by default try to add a probename suffix to each result
]
required_pars = []
# optional parameters
for parname, attname, partype, default in optional_pars:
try:
val = params[parname]
if partype == 'boolean':
if isinstance(val, str):
val = val.lower() in ['1', 'true', 'y', 'yes']
elif partype == 'int':
val = int(val)
elif partype == 'stringint4':
val = [int(v) for v in val.split(';')]
setattr(cs, attname, val)
except:
if not default is None: # only if a default value is given
setattr(cs, attname, default)
# optional parameters
#required
for parname, attname, partype in required_pars:
val = params[parname]
if partype == 'boolean':
if isinstance(val, str):
val = val.lower() in ['1', 'true', 'y', 'yes']
elif partype == 'int':
val = int(val)
elif partype == 'stringint4':
val = [int(v) for v in val.split(';')]
setattr(cs, attname, val)
return qclib, cs
def OCR(data, results, action, idname):
"""
Use pyOCR which for OCR
returns rect rois for plotting in overview
If results is None, just return the OCR content, do not add to results
"""
try:
params = action['params']
except KeyError:
params = {}
# optional parameters
ocr_options = {}
for lab in ['ocr_threshold', 'ocr_zoom', 'ocr_border']:
if lab in params:
ocr_options[lab] = int(params[lab])
inputfile = data.series_filelist[0] # give me a [filename]
rgbchannel = params.get('rgbchannel', 'B')
dcmInfile, pixelData, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag(), rgbchannel=rgbchannel)
# find probename
idname = ''
if params.get('auto_suffix', False):
if idname is None:
idname = '_' + qc.imageID(probeonly=True)
# add pluginversion to 'result' object
add_plugin_version(qc, results, 'pluginversion' + idname)
rectrois = []
error = False
msg = ''
values = {}
# solve ocr params
ocr_regions = params.get('ocr_regions', {}) # new format
regions = {}
for ocrname, ocrparams in ocr_regions.items():
regions[ocrname] = {'prefix': '', 'suffix': ''}
for key, val in ocrparams.items():
if key == 'xywh':
regions[ocrname]['xywh'] = [int(p) for p in val.split(';')]
elif key == 'prefix':
regions[ocrname]['prefix'] = val
elif key == 'suffix':
regions[ocrname]['suffix'] = val
elif key == 'type':
regions[ocrname]['type'] = val
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(pixelData, region['xywh'], **ocr_options)
uname = name + str(idname)
if region['type'] == 'object':
im = toimage(part)
fn = '{}.jpg'.format(uname)
im.save(fn)
results.addObject(uname, fn)
else:
try:
value = ocr_lib.txt2type(txt, region['type'], region['prefix'],
region['suffix'])
if not results is None:
if region['type'] == 'float':
results.addFloat(uname, value)
elif region['type'] == 'string':
results.addString(uname, value)
elif region['type'] == 'bool':
results.addBool(uname, value)
else:
values[uname] = value
except:
print("error", uname, value)
error = True
msg += uname + ' '
im = toimage(part)
fn = '{}.jpg'.format(uname)
im.save(fn)
if results is None:
return values, error, msg
return rectrois, error, msg
def qc_series(data, results, action, idname):
"""
US Reverberations in Air analysis:
Check the uniformity of the reverberation patterns
Params needs to define:
nothing yet
Workflow:
1. Set runtime parameters
2. Check data format
3. Build and populate qcstructure
4. Run tests
5. Build xml output
6. Build artefact picture thumbnail
"""
# 1.-3.
try:
params = action['params']
except KeyError:
params = {}
inputfile = data.series_filelist[0] # give me a [filename]
wrapper_params = [
'rgbchannel',
'auto_suffix',
] # parameters for wrapper only
rgbchannel = params.get('rgbchannel', 'B')
dcmInfile, pixelData, dicomMode = wadwrapper_lib.prepareInput(
inputfile, headers_only=False, logTag=logTag(), rgbchannel=rgbchannel)
# correct data order wadwrapper_lib return x,y data
if len(pixelData.shape) == 2:
pixelData = np.transpose(pixelData, (1, 0))
elif len(pixelData.shape) == 3:
pixelData = np.transpose(pixelData, (0, 2, 1))
qc = QCUS2_lib.Analysis(dcmInfile, pixelData)
for name, value in params.items():
if not name in wrapper_params:
qc.set_param(name, value)
qc.run()
if GUIMODE:
qc.show_report()
print("Result in {}".format(os.getcwd()))
matplotlib.pyplot.show()
# find probename
idname = ''
if params.get('auto_suffix', False):
if idname is None:
idname = '_' + qc.imageID(probeonly=True)
# add pluginversion to 'result' object
add_plugin_version(qc, results, 'pluginversion' + idname)
# add results to 'result' object
report = qc.get_report()
for section in report.keys():
for key, vals in report[section].items():
if vals[0] in ['int', 'float']:
results.addFloat(key + idname, vals[1])
elif vals[0] in ['string']:
results.addString(key + idname, vals[1])
elif vals[0] in ['bool']:
results.addBool(key + idname, vals[1])
elif vals[0] in ['object']:
results.addObject(key + idname, vals[1])
else:
raise ValueError(
"Result '{}' has unknown result type '{}'".format(
key, vals[0]))
return qc # for write_images
def qc_uniformity_series(data, results, action):
"""
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
"""
try:
params = action['params']
except KeyError:
params = {}
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())
# select only middle slice for series
numslices = len(pixeldataIn)
if dicomMode == wadwrapper_lib.stMode3D:
nim = int(len(pixeldataIn)/2.)
dcmInfile = dcmInfile._datasets[nim]
pixeldataIn = np.average(pixeldataIn, axis=0)
dicomMode = wadwrapper_lib.stMode2D
## 3. Build and populate qcstructure
remark = ""
qclib = n13_lib.XRayQC()
room = _getRoomDefinition(params, "unif")
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 = 'artefacts'
filename = '%s%s.jpg'%(label,idname) # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename, 'artefacts')
varname = '%s%s'%(label,idname)
results.addObject(varname, filename)
## also add uniformity thumbnail
label = 'uniformity'
filename = '%s%s.jpg'%(label,idname) # Use jpg if a thumbnail is desired
qclib.saveAnnotatedImage(cs, filename, 'uniformity')
varname = '%s%s'%(label,idname)
results.addObject(varname, filename)
labvals = qclib.ReportEntries(cs)
tmpdict={}
for elem in labvals:
varname = elem['name']+str(idname)
results.addFloat(varname, elem['value'])
results.addFloat('num_slices'+str(idname), numslices)
