Development of Accelerated Raman Scattering and Fluorescent Monte Carlo Model

摘要

Monte Carlo (MC) modeling of photon propagation in turbid media is an essential tool for understanding optical interactions between light and tissue. Insight gathered from outputs of MC models assists in mapping between detected optical signals and bulk tissue optical properties, and as such, has proven useful for inverse calculations of tissue composition and optimization of the design of optical probes. MC models of Raman scattering have previously been implemented without consideration to background autofluorescence, despite its presence in raw measurements. Modeling both Raman and fluorescence profiles at high spectral resolution requires a significant increase in computation, but is more appropriate for investigating issues such as detection limits. We present a new Raman Fluorescence MC model developed atop an existing GPU parallelized MC framework that can run more than 300x times faster than CPU methods. The robust acceleration allows for the efficient production of both Raman and fluorescence outputs from the MC model. In addition, this model can handle arbitrary sample morphologies of excitation and collection geometries to more appropriately mimic experimental settings. We will present the model framework and initial results.