This function is the constructor of Monte Carlo Backscattering (MCBS) class. Diffuse reflection, also called as backscattering, is the phenomena when light enters into the media, such as biological tissue, and after traveling some distance it leaves the media or tissue through the surface.
MCBS(myTissue,myLight)collection of optical parameters of the semi-infinite medium. It is a list of numbers: c(mua,mus,g,n) as absorption coefficient (1/cm), scattering coefficient (1/cm), anisortopy factor, refractive index.
collection of computational parameters. It is a list of numbers: c(photons,beamradius,limitingenergy,haloradius,resolution) as number of photons used in calculation, radius of incident light beam (cm), photon energy threshold to stop tracing if energy decreased too much, radius of surface area where photon flux is collected (cm), spatial resolution (cm/pixel). Due to the simulation of optical measurement, spatial resolution is expressed on the basis of pixel (px).
The MCBS function returns an object of class. Package functions are used to access their parameters for reporting, adjustment and computation. Direct manipulation of object parameters is highly not recommended. Please use the provided functions to reach what is necessary or use them read-only.
An object of class "MCBS" is a list containing at least the following components:
absorption coeffieint, 1/cm
scattering coefficient, 1/cm
anisotropy factor
relative refractive index of media (the other media is assumed to be air)
transport albedo, the descrease of photon energy after one absorption event in media. The value is initialized by Setup function.
cosine of critical angle. The value is initialized by Setup function.
specular reflection. The value is calculated on the basis of refractive index by Setup function.
The MCBS function creates and initializes a class using the given parameters. The two arguments are separated according to their role. The first one describes media in which photons travel. The second defines simulation parameters. See arguments for details.
The optical parameters describing observed media typically has the relationship of mua << mus, which means absorption coefficient is much smaller that scattering coefficient. Many research papers publish the reduced scattering coefficient rmus = mus*(1-g). The general problem of comparison and validation is that list(mus=2,g=0) results the same reduced scattering coefficient like list(mus=20,g=0.9). The value of g shows the most likely direction of light after interaction event in media: g = 1 means continue forward, g = 0 means there is no expected direction and media is isotropic, g = -1 means reflected backward. In biological tissues, anisotropy factor (g) is reported to be in the range of 0.8 - 0.99.
Since argument myLight is reflecting measurement conditions and hardware setup, it can be considered constant for one system. Please note that quality of results depends on the number of photons. The more is used the better quality you get. The minimum suggested number is 100,000 photons. If you calculate the amount of photons with sensor or camera integration time, this number will increase above billion.
The argument myTissue includes optical parameters of the sample, this is expected to change during experiment such as storage, grading, etc.
Jacques, S.L. (1998) Light Distributions from Point, Line and Plane Sources for Photochemical Reactions and Fluorescence in Turbid Biological Tissues. Photochemistry and Photobiology, 67(1): 23-<U+2013>32. 10.1111/j.1751-1097.1998.tb05161.x.
Wang, L., Jacques, S.L., Zheng, L. (1995) MCML <U+2013> Monte Carlo modeling of light transport in multi-layered tissues. Computer Methods and Programs in Biomedicine, 47: 131-<U+2013>146. 10.1016/0169-2607(95)01640-F.
Wang, L., Jacques, S.L., Zheng, L. (1997) CONV-convolution for responses to a finite diameter photon beam incident on multi-layered tissues. Computer Methods and Programs in Biomedicine, 54: 141<U+2013>-150. 10.1016/S0169-2607(97)00021-7.
Zo<U+0142>ek, N.S., Liebert, A., Maniewski, R. (2006) Optimization of the Monte Carlo code for modeling of photon migration in tissue. Computer Methods and Programs in Biomedicine, 84: 50<U+2013>-57. 10.1016/j.cmpb.2006.07.007.
Baranyai, L., Zude, M. (2009) Analysis of laser light propagation in kiwifruit using backscattering imaging and Monte Carlo simulation. Computers and Electronics in Agriculture, 69: 33-<U+2013>39. 10.1016/j.compag.2009.06.011.
Baranyai, L. (2020) Laser induced diffuse reflectance imaging <U+2013> Monte Carlo simulation of backscattering measured on the surface. MethodsX, 7: 100958. 10.1016/j.mex.2020.100958.
Setup for initial computation of specular reflection and transport albedo.
Randomize for adjustment of random trajectory vectors.
Simulation for running the simulation with adjusted parameters.
print show adjusted parameters and total backscattered reflection.
Chart for plot of calculated photon flux profile.
Export for export of photon flux with corresponding radii.
# NOT RUN {
## Apple simulation data according to Qin and Lu (2006).
## DOI: 10.13031/2013.20862
cfgMedia <- c(
0.63, # absorption, 670 nm
30, # reduced scattering, 670 nm
0, # isotropic tissue assumed
1.4) # refractive index
cfgSimulation <- c(
1e6, # 1 million photons
0.05, # 1 mm diameter (0.05 cm radius) laser light beam
1e-9, # limiting energy level
3, # 3 cm radius is computed
0.012) # 0.012 cm/pixel resolution is assumed
apple <- MCBS(cfgMedia,cfgSimulation)
cfgMedia <- c(
0.63, # absorption, 670 nm
300, # scattering, 670 nm
0.9, # anisotropic tissue with forward scattering is assumed
1.4) # refractive index
apple <- MCBS(cfgMedia,cfgSimulation)
# }
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