def runOneSimulation(wavelength, eHbO2, eHb,
infile, simulationOutputFolderName, gpumcmlDirectory, gpumcmlExecutable,
BVF=0.1, Vs=0.4, d=500 * 10**-6,
r=0.4 * 10**-6, SaO2=0.7, cHb=120,
submucosa_BVF=0.1, submucosa_Vs=0.3, submucosa_r = 2*10**-6, submucosa_SaO2=0.7,
Fwhm = 20 * 10**-9, nrPhotons = 10**6,
):
"""
Args:
_____
cHb:
concentration of haemoglobin per unit volume of blood in colon [g/L],
taken from: "Modelling and validation of spectral reflectance for the colon"
"""
outputFilename = \
simulationOutputFolderName + \
"BVF" + repr(BVF) + \
"Vs" + repr(Vs) + \
"d" + repr(d) + \
"SaO2" + repr(SaO2) + \
"r" + repr(r) + \
"photons" + repr(nrPhotons) + \
"wavelength" + repr(wavelength) + \
".mco"
usg = mieMonteCarlo.mieMonteCarlo_FWHM(wavelength, r, Vs, FWHM = Fwhm)
ua = calcUa(BVF, cHb, SaO2, eHbO2, eHb, wavelength)
# calculate ua, us for submucosa, values taken from
# "Model based inversion for deriving maps of
# histological parameters characteristic of cancer
# from ex-vivo multispectral images of the colon"
ua_sm = calcUa(submucosa_BVF, cHb, submucosa_SaO2, eHbO2, eHb, wavelength)
usg_sm = mieMonteCarlo.mieMonteCarlo_FWHM(wavelength,submucosa_r, submucosa_Vs, FWHM = Fwhm)
# now create us and ua for muscle layer according to
# "Modelling and validation of spectral reflectance for the colon"
us_mus = calcUsMuscle(wavelength)
A = 1.7923385088285804 # calculated to retrieve an absorption of 11.2 cm-1
# at 515nm
ua_mus = calcUa(A*0.1, 120, 0.7, eHbO2, eHb, wavelength)
# factors are due to the program expecting [cm] instead of [m]
replacements = {'muc_c_ua':str(ua / 100), 'muc_c_us':str(usg['us'] / 100),
'muc_c_g':str(usg['g']), 'muc_c_d':str(d * 100),
'sm_c_ua':str(ua_sm / 100), 'sm_c_us':str(usg_sm['us'] / 100),
'sm_c_g':str(usg_sm['g']),
'mus_c_ua':str(ua_mus / 100), 'mus_c_us':str(us_mus / 100),
'outputFilename':outputFilename,
'c_ph': str(nrPhotons)}
createSimulationFile(infile, replacements,
systemPaths.getOutputFolder() + "simulationFile.mci")
args = ("./" + gpumcmlExecutable, "-A", systemPaths.getOutputFolder() + "simulationFile.mci")
with cd(gpumcmlDirectory):
popen = subprocess.Popen(args, stdout=subprocess.PIPE)
popen.wait()
# outside the context manager we are back wherever we started.
# this function is error prone, please refer to documentation to see
# if problematic for you
return getReflectanceFromFile(gpumcmlDirectory + outputFilename)
parameterImage_i = np.reshape(result[:,i], shape)
im = Image.fromarray(parameterImage_i)
im.save(dataFolder + imageName + "_parameterImage_" + str(i) + ".tiff")
with open(dataFolder + "result_" + imageName + '.csv', 'wb') as csvfile:
spamwriter = csv.writer(csvfile, delimiter=';',
quotechar='|', quoting=csv.QUOTE_MINIMAL)
spamwriter.writerow([imageName])
spamwriter.writerow(['r2Score', str(r2Score)])
# the folder with the reflectance spectra
dataFolder = systemPaths.getOutputFolder()
##%% Evaluate CC2 Mitte links data
#imageToLoad = "CC2_links"
#
#
###%% get data
#trainingParameters, trainingReflectances, shape, image, trainsegmentation, testsegmentation = \
# data.realImage(dataFolder, imageToLoad)
#
####%% do evaluation with out domain adaptation
#resName = imageToLoad + "_NODA"
#resultCC2linksNODA, r2ScoreCC2linksNODA, backProjectedReflectancesCC2linksNODA, realReflectanceCC2linksNODA = estimateParametersRealImage(trainingParameters, trainingReflectances, shape, image, trainsegmentation, testsegmentation, False)
#saveResults(resultCC2linksNODA, shape, r2ScoreCC2linksNODA, dataFolder, resName)
def runOneSimulation(
wavelength,
eHbO2,
eHb,
infile,
simulationOutputFolderName,
gpumcmlDirectory,
gpumcmlExecutable,
BVF=0.1,
Vs=0.4,
d=500 * 10**-6,
r=0.4 * 10**-6,
SaO2=0.7,
cHb=120,
submucosa_BVF=0.1,
submucosa_Vs=0.3,
submucosa_r=2 * 10**-6,
submucosa_SaO2=0.7,
Fwhm=20 * 10**-9,
nrPhotons=10**6,
):
"""
Args:
_____
cHb:
concentration of haemoglobin per unit volume of blood in colon [g/L],
taken from: "Modelling and validation of spectral reflectance for the colon"
"""
outputFilename = \
simulationOutputFolderName + \
"BVF" + repr(BVF) + \
"Vs" + repr(Vs) + \
"d" + repr(d) + \
"SaO2" + repr(SaO2) + \
"r" + repr(r) + \
"photons" + repr(nrPhotons) + \
"wavelength" + repr(wavelength) + \
".mco"
usg = mieMonteCarlo.mieMonteCarlo_FWHM(wavelength, r, Vs, FWHM=Fwhm)
ua = calcUa(BVF, cHb, SaO2, eHbO2, eHb, wavelength)
# calculate ua, us for submucosa, values taken from
# "Model based inversion for deriving maps of
# histological parameters characteristic of cancer
# from ex-vivo multispectral images of the colon"
ua_sm = calcUa(submucosa_BVF, cHb, submucosa_SaO2, eHbO2, eHb, wavelength)
usg_sm = mieMonteCarlo.mieMonteCarlo_FWHM(wavelength,
submucosa_r,
submucosa_Vs,
FWHM=Fwhm)
# now create us and ua for muscle layer according to
# "Modelling and validation of spectral reflectance for the colon"
us_mus = calcUsMuscle(wavelength)
A = 1.7923385088285804 # calculated to retrieve an absorption of 11.2 cm-1
# at 515nm
ua_mus = calcUa(A * 0.1, 120, 0.7, eHbO2, eHb, wavelength)
# factors are due to the program expecting [cm] instead of [m]
replacements = {
'muc_c_ua': str(ua / 100),
'muc_c_us': str(usg['us'] / 100),
'muc_c_g': str(usg['g']),
'muc_c_d': str(d * 100),
'sm_c_ua': str(ua_sm / 100),
'sm_c_us': str(usg_sm['us'] / 100),
'sm_c_g': str(usg_sm['g']),
'mus_c_ua': str(ua_mus / 100),
'mus_c_us': str(us_mus / 100),
'outputFilename': outputFilename,
'c_ph': str(nrPhotons)
}
createSimulationFile(infile, replacements,
systemPaths.getOutputFolder() + "simulationFile.mci")
args = ("./" + gpumcmlExecutable, "-A",
systemPaths.getOutputFolder() + "simulationFile.mci")
with cd(gpumcmlDirectory):
popen = subprocess.Popen(args, stdout=subprocess.PIPE)
popen.wait()
# outside the context manager we are back wherever we started.
# this function is error prone, please refer to documentation to see
# if problematic for you
return getReflectanceFromFile(gpumcmlDirectory + outputFilename)