Light Propagation in Biological tissue using Monte Carlo Simulation

摘要

Non-invastve diagnosis is medicine has shown considerable attention in recent years. Several methods are already available for imaging the biological tissue like X-ray computerized tomography, magnetic resonance imaging and ultrasound imaging etc. But each has its own disadvantages. Optical tomography is one of the emerging methods in the field of medical imaging which is non-invasive in nature. The only problem that occurs in using light for imaging the tissue is that it is highly scattered inside tissue, so the propagation of light in tissue is not confined to straight lines as the case with X-ray tomography. So the need arises to understand the behavior of propagation of light in tissue. There are several methods for light interaction with tissue. These methods can be divided into two categories viz. deterministic methods and stochastic methods. Deterministic methods involve the solution of radiative transfer equation (RTE) which is complex integrodifferential equation and is difficult to solve. Stochastic methods model the RTE through dealing individual interaction. The individual interactions are modeled explicitly by deriving probability density functions in random walk and Markov random field models. Monte Carlo method is stochastic method which is simple technique for simulation of light through tissue, In the Monte Carlo methods individual history of photons is simulated as they undergo scattering and absorption events in the biological tissue. This is continued until the photon is either absorbed or is emitted from the boundary of the tissue. The data obtained from the Monte Carlo simulation is the number of photons detected at different times which is known as temporal point spread function(TPSF), This TPSF is used by nonlinear optimization techniques to get the reconstruction of image.