def check_overlap(self,newsphere):
a = newsphere.volume
for key in self.bgspheres.keys():
b = self.bgspheres[key].volume
if niq.compare_coordsets(a,b) == True:
return None
return newsphere
def __init__(self,data,order=['x','y','z'],phantomdim=[20,10],phantomvolume=9500,dose=75,dosecaltime='000000',remdose=0,remdosecaltime='000000'):
print order
self.xind = order.index('x')
self.yind = order.index('y')
self.zind = order.index('z')
axes = [self.xind,self.yind,self.zind]
print data
pixelsize,array,info = niq.loaddata(data)
print info
self.pixel_size = pixelsize
print "pixelsize: ", pixelsize
self.phantomvolume = float(phantomvolume)
self.dose = float(dose)
self.dosecaltime = str(dosecaltime)
self.remdose = float(remdose)
self.remdosecaltime = str(remdosecaltime)
self.rows = info.info["0028","0010"].value
self.cols = info.info["0028","0011"].value
self.vendor = info.info["0008","0070"].value
if self.vendor == 'Philips Medical Systems':
self.suvfactor = info.info["7053","1009"].value
else:
self.suvfactor = 1.0
self.weight = info.info["0010","1030"].value
print "Acquisition date",info.info["0008","0022"].value #Date
acqtime = info.info["0008","0032"].value.split('.')[0] #Acq. Time and we remove the microseconds
print "Acquisition time: ", acqtime
print "Activity calibrated: %s at %s "%(self.dose,self.dosecaltime)
print "Remainder activity: %s at %s "%(self.remdose,self.remdosecaltime)
self.fmt = '%H%M%S'
self.fmt2 = '%H%M'
t1 = datetime.strptime(acqtime, self.fmt) #acquisition time dcmhdr
t2 = datetime.strptime(self.dosecaltime, self.fmt) #act. cal time
t3 = datetime.strptime(self.remdosecaltime, self.fmt)#remaining activity cal time
# Activity concentration at acquisitiontime:
deltat0 = float((t1 - t2).seconds/60.) #minutes
deltatr = float((t2 - t3).seconds/60.) #minutes
self.currconc = niqlib.calc_act_con(self.phantomvolume,self.dose,deltat0,self.remdose,deltatr)
print "Net activity at acquisition : %s "%self.currconc
def __init__(self,data,order=['x','y','z'],phantomdim=[20,10],phantomvolume=9500,dose=75,dosecaltime='000000',remdose=0,remdosecaltime='000000'):
print order
self.xind = order.index('x')
self.yind = order.index('y')
self.zind = order.index('z')
axes = [self.xind,self.yind,self.zind]
print data
pixelsize,array,info = niq.loaddata(data)
print info
self.pixel_size = pixelsize
print "pixelsize: ", pixelsize
self.phantomvolume = float(phantomvolume)
self.dose = float(dose)
self.dosecaltime = str(dosecaltime)
self.remdose = float(remdose)
self.remdosecaltime = str(remdosecaltime)
self.rows = info.info["0028","0010"].value
self.cols = info.info["0028","0011"].value
print "info - date",info.info["0008","0022"].value #Date
acqtime = info.info["0008","0032"].value.split('.')[0] #Acq. Time and we remove the microseconds
print "acquisition time: ", acqtime
print "acquisition time: ", self.dosecaltime
print "acquisition time: ", self.remdosecaltime
self.fmt = '%H%M%S'
self.fmt2 = '%H%M'
t1 = datetime.strptime(acqtime, self.fmt) #acquisition time dcmhdr
t2 = datetime.strptime(self.dosecaltime, self.fmt) #act. cal time
t3 = datetime.strptime(self.remdosecaltime, self.fmt)#remaining activity cal time
# Activity concentration at acquisitiontime:
deltat0 = float((t1 - t2).seconds/60.) #minutes
deltatr = float((t2 - t3).seconds/60.) #minutes
self.currconc = self.calc_act_con(self.phantomvolume,self.dose,deltat0,self.remdose,deltatr)
print self.currconc
#float(indata.info["0028","0030"].value[0])
self.bgradius = 4
self.data = np.array(array)
print type(self.data)
print type(self.data[0])
tmpshape = np.shape(self.data)
print tmpshape
self.ddimz = tmpshape[self.zind]
self.ddimy = tmpshape[self.yind]
self.ddimx = tmpshape[self.xind]
self.maxdata = self.data.max()
self.volume = np.zeros(np.shape(data))
# self.mode = mode
self.z = self.z_init()
self.thrdata = copy.deepcopy(self.data)
lowind = (self.thrdata < np.max(self.thrdata[self.z,:,:])*0.2)
self.thrdata[lowind] = 0.0
highind = (self.thrdata >= np.max(self.thrdata[self.z,:,:])*0.2)
self.thrdata[highind] = 10
self.bgdata = copy.deepcopy(self.data)
self.roughcom = ndimage.measurements.center_of_mass(self.data[self.z,:,:])
print "rough com location:", self.roughcom
self.cor = self.roughcom
self.bgspheres = {}
self.set_bg_spheres()
def get_earliq(self, filename, mode, axorder, sporder):
inputdict = self.get_input_pars()
self.curr_results = NEMAIQ.update_wad(filename, mode, axorder, sporder,
**inputdict)
def get_earliq(self):
print '-'*20
print 'The following earl results have been found:'
results = {}
for row in ['NM_EARL_SUV','NM_EARL_IQ']:
results[row] = []
tmpresults = []
for elem in self.analyseoutput:
if row in elem[1]:
tmpresults.append(elem)
#print 'Aanwezige resultaten:',tmpresults
datelist = []
for elem in tmpresults:
datelist.append([int(elem[1].split('/')[1]),int(elem[0])])
#print "datelist: ", sorted(datelist) #.sort(key=itemgetter(0))
for elem in sorted(datelist):
tmppk = elem[1]
self.cur.execute("SELECT * from gewenste_processen where analysemodule_output_fk = %s"%tmppk)
output = self.cur.fetchall()[0]
self.cur.execute("SELECT * from resultaten_char where gewenste_processen_fk = %s"%output[0])
limits = self.cur.fetchall()
for subelem in limits:
if subelem[2] == 'status':
results[row].append([output[5],subelem[2],subelem[5],subelem[1]])
print '--RESULTATEN--:'
for key in results.keys():
print key
for nr, subresult in enumerate(results[key]):
print '\t',nr, subresult
selection = {}
# we select a result
#print 'selecting 2014-7-5 15:48:47 gewenste_pk = 30'
print 'Voer het gewenste procesnr in:'
gewenste_pk = raw_input()
print 'Je voerde in %s, indien correct voer 0 in'%gewenste_pk
tmpstatus = raw_input()
if tmpstatus == '0':
pass
else:
sys.exit()
selection['gewenste_pk'] = gewenste_pk
selection['type'] = 'NM_EARL_SUV'
# from the gewenste processen key we obtain the analysemodule_input key
self.cur.execute("SELECT * from gewenste_processen where pk = %s"%str(gewenste_pk))
tmpoutkey = self.cur.fetchall()[0][8]
print 'tmpselectorkey',tmpoutkey
#from the analyse_output key we obtain the file
self.cur.execute("SELECT * from analysemodule_input where pk = %s"%str(tmpoutkey))
tmpoutput = self.cur.fetchall()[0]
#set the base dir
tmpxml = os.path.join('D:\WAD-software',tmpoutput[2],tmpoutput[1])
import xml.etree.ElementTree as ET
tree = ET.parse(tmpxml)
root = tree.getroot()
pat = tree.findall('patient')[0]
stud = pat.findall('study')[0]
ser = stud.findall('series')[0]
ins = ser.findall('instance')[0]
fil = ins.getchildren()[1].text
#,self.cur.fetchall()[0][2])
print 'resultaat voor keuze', fil
seriesdir = os.path.split(fil)[0]
#now that we have the series we can launch the tool
#first we ask the necessary pars
m = 'max'
order = 'zxy'
ort = 'acw'
bga = 10.0
spa = 1.0
if selection['type'] == 'NM_EARL_IQ':
results['EARL IQ'] = NEMAIQ.update_wad(filename = seriesdir, mode = m, axorder = order, sporder = ort,bgac = bga, sphereac = spa)
elif selection['type'] == 'NM_EARL_SUV':
results['EARL SUV'] = NEMASUV.update_wad(filename = seriesdir, mode = m, axorder = order, sporder = ort,bgac = bga, dimensions = [15,5], volume = '9200', caltime=120000 , remainder=0, remtime= 120000)
print "write to database"
for key in results.keys():
print key, results[key]
print "updating float results"
self.cur.execute("SELECT * from resultaten_floating where gewenste_processen_fk = %s"%str(selection['gewenste_pk']))
tmpfloats = self.cur.fetchall()
for elem in tmpfloats:
print 'parameter',elem[2],'value', elem[7], 'updating to' , results[elem[2]]
print "updating char results"
self.cur.execute("SELECT * from resultaten_char where gewenste_processen_fk = %s"%str(selection['gewenste_pk']))
tmpchar = self.cur.fetchall()
for elem in tmpchar:
print 'parameter',elem[2],'value', elem[5], 'updating to' , results[elem[2]]
print "updating image results"
self.cur.execute("SELECT * from resultaten_object where gewenste_processen_fk = %s"%str(selection['gewenste_pk']))
tmpfig = self.cur.fetchall()
for elem in tmpfig:
print 'parameter',elem[2],'value', elem[5], 'updating to', results[elem[2]]
print "setting status to processed"
self.cur.execute("update resultaten_char set waarde='processed' where gewenste_processen_fk=%s"%str(gewenste_pk))
self.db.commit()
