Monte Carlo Simulation Of Detecting The Inner Information Of Multi-layered Biological Tissue Based On Spatially Resolved Diffuse Reflectance Technology

The structural characteristics and physiological characteristics of biological tissue have a significant relationship with our health,and However,in most methods of detecting the inner information of inhomogeneous tissue,a significant issue is that the detection position is ambiguous because of the complexity of human tissue structure and discrepancies among individuals.Thus the aim of this paper is to study the best source-detector separation(SDSbest)to detect the internal information of a fat-muscle tissue with spatially resolved diffuse reflectance spectra.Firstly,study on internal information of a fat-muscle tissue by optimizing the detection range.The spatially resolved diffuse reflectance spectra was investigated to estimate the optimal detection range [SDScri_min,SDScri_max] by balancing the relation between reflectance intensity I,which was obtained by modified Monte Carlo simulation and included non-target reflectance intensity I(zf,ri) and target reflectance intensityI(zm,ri),and self-defined SNR,which was useful to extract desired information from the target layer and to decrease the interference from the non-target layer.Secondly,study on internal information of the fat-muscle tissue by optimizing the detection position.In order to weaken the measurement error caused by the discrepancies among individuals and multiple backscattered photons,and according to the transmission model of light in complex biological tissue,then we added the constraint condition---two ideal ?banana shape? paths---to define the effective photon ration(SNR),and we selected the best source-detector separations(SDSbest)by SNR,and the results from Monte Carlo simulation modified by adding constraint condition were statistically analyzed,and we regard the SNR as evaluation criterion and analyze the relationship between the fat thickness(hf),the absorption coefficient of a fat layer(?af),the absorption coefficient of a muscle layer(?am)and the source-detector distance(SDS),and hf is used as the independent variable to develop a linear regression model to predict SDSbest..Finally,study the effect of the multiple backscattered from the target layer on the best source-detector separations,to this aim,we had introduced a variable parameter k,which was applied to simulate a spatial filter,which was used to reject multiply scattered photons.Firstly,study the influence of k on the relationship between the non-effective signal and the source-detector separations(SDS)when fat thickness varied from 0.1cm~0.55 cm.Secondly,study the influence of k on the relationship between hf and SDSbest.This method can select the SDSbest much easier and faster to detect the inner information of turbid tissue,and realize to weaken the interference from the non-target layer and multiple backscattered photons.