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)