Estimation of quasi-straightforward propagating light in tissues

Abstract

We have developed a controlled Monte Carlo (CMC) method to calculate the time-dependent transmittance of light through a thick tissue, especially for evaluation of the contribution from early arriving photons. Quasi-straightforward propagating trajectories are favoured according to a selection mechanism, so adequate trajectories of interest can reach the detector, improving the statistics dramatically. Simulations were conducted for tissue models with a thickness of 3-5 cm, and with optical properties similar to human breast tissue. Temporal profiles of early transmittance were obtained with satisfactory convergence. In addition, comparison was made with the conventional Monte Carlo approach to verify our scheme when applied to cases of optically thin tissues.

Improved importance sampling for Monte Carlo simulation of time-domain optical coherence tomography

“…This importance sampling implementation is comparable to the bias procedure described in [10,11], except in the way in which the biasing of the scattering angle is implemented. In our method, the angles are deterministically biased towards the preferred direction, and the scattered photon packets are weighted by the corresponding likelihood ratio that eliminates any residual statistical bias.…”

“…In our method, the angles are deterministically biased towards the preferred direction, and the scattered photon packets are weighted by the corresponding likelihood ratio that eliminates any residual statistical bias. In the method in [10,11], the scattering direction is chosen using the standard Henyey-Greenstein probability function in Eq. (1), but the actual scattering direction is rejected as many times as necessary until an acceptable direction closer to the direction of the source is chosen.…”

“…(1), but the actual scattering direction is rejected as many times as necessary until an acceptable direction closer to the direction of the source is chosen. Therefore, the method in [10,11] requires considerable additional computational time per biased scattering event. We note that this computational time increases with the bias strength, since the probability of rejection of the scattering directions increases with the amount of bias.…”

“…It has been demonstrated that Class II diffuse reflectance is the fundamental limitation in increasing the imaging depth of OCT in tissue [7]. Understanding the physical process governing both Class I and Class II diffusive reflectance is an important prerequisite to any effort to increase penetration depth and to enhance the quality of the images obtained with OCT. As this physical process is complicated, Monte Carlo simulation of light transport in tissue [8][9][10][11] has been used to obtain the TD-OCT signal [5].…”

“…This importance sampling method applies multiple biases in the direction of photon scattering towards the apparent position of the OCT collecting fiber. To eliminate the residual statistical bias on the Class I diffusive reflectance in the range of interest that are present in the previously reported methods [5,10,17], which underestimates the diffuse reflectance, we developed a photon packet splitting procedure at the location of each biased backscatter [19]. Our method enables an accurate calculation of the TD-OCT signal at all depths about one thousand times faster than the standard Monte Carlo method.…”