Monte Carlo Simulation for Raman Spectroscopy System Analysis

Raman hyperspectral imaging is limited by its time-consuming nature. Accelerating acquisition time without sacrificing image integrity often includes collecting fewer spectra and accounting for missing data with interpolation. The unique parameters of each experiment make it challenging to generalize the measurements required to accurately represent a sample. A tool predicting the limits of resolution in hyperspectral imaging would save time and make Raman results more accessible to those without expertise in hyperspectral imaging techniques.

We created a Monte Carlo simulation modeling the intensity of Raman signal from a small target within a scattering medium. This simulates sixteen variables, including target size, scattering coefficient, and the relative position of the target, sensor, and laser. The flexibility of the simulation allows us to predict parameters that would result in fast acquisition times while still accurately representing the sample. Comparing results from the simulation with experimental data collected from tissue phantoms demonstrates the practicality of employing the Monte Carlo model to choose experimental parameters. Further development would create a diagnostic tool to provide rapid analysis of the performance of simulated Raman spectroscopy systems.