Modeling diffuse reflectance from homogeneous semi-infinite turbid media for biological tissue applications: a Monte Carlo study

George Zonios,Aikaterini Dimou

doi:10.1364/boe.2.003284

Abstract

Diffuse reflectance spectroscopy is one of the simplest and widely used techniques for the non-invasive study of biological tissues but no exact analytical solution exists for the problem of diffuse reflectance from turbid media such as biological tissues. In this work, a general treatment of the problem of diffuse reflectance from a homogeneous semi-infinite turbid medium is presented using Monte Carlo simulations. Based on the results of the Monte Carlo method, simple semi-empirical analytical solutions are developed valid for a wide range of collection geometries corresponding to various optical detector diameters. This approach may be useful for the quick and accurate modeling of diffuse reflectance from tissues.

Highlights

Many studies in biomedical optics have employed diffuse reflectance spectroscopy for the non-invasive characterization and analysis of biological tissues
No exact analytical solution exists for the problem of light propagation in turbid media such as biological tissues
Several studies have introduced relatively simple models, which are designed for specific probe geometries [3,4], with some of them being empirical or semi-empirical in nature while others are based on a relatively simple solution of the diffusion approximation utilizing the method of images [5]

Summary

Introduction

Many studies in biomedical optics have employed diffuse reflectance spectroscopy for the non-invasive characterization and analysis of biological tissues. Several studies have introduced relatively simple models, which are designed for specific probe geometries [3,4], with some of them being empirical or semi-empirical in nature while others are based on a relatively simple solution of the diffusion approximation utilizing the method of images [5]. Significant acceleration using graphics processing units (GPU) has been possible [10,11,12]. Overall, these improvements yield an advantage of several orders of magnitude faster execution, making MC simulations a very appealing technique. At least one study has recently been published utilizing a MC method in the forward mode in lieu of an analytical solution [13]

Methods

Results

Discussion

Conclusion