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A computationally efficient Monte-Carlo model for biomedical Raman spectroscopy
Authors:Alexander P. Dumont  Qianqian Fang  Chetan A. Patil
Affiliation:1. Department of Bioengineering, Temple University, Philadelphia, Pennsylvania, USA;2. Department of Bioengineering, Northeastern University, Boston, Massachusetts, USA
Abstract:Monte Carlo (MC) modeling is a valuable tool to gain fundamental understanding of light-tissue interactions, provide guidance and assessment to optical instrument designs, and help analyze experimental data. It has been a major challenge to efficiently extend MC towards modeling of bulk-tissue Raman spectroscopy (RS) due to the wide spectral range, relatively sharp spectral features, and presence of background autofluorescence. Here, we report a computationally efficient MC approach for RS by adapting the massively-parallel Monte Carlo eXtreme (MCX) simulator. Simulation efficiency is achieved through “isoweight,” a novel approach that combines the statistical generation of Raman scattered and Fluorescence emission with a lookup-table-based technique well-suited for parallelization. The MC model uses a graphics processor to produce dense Raman and fluorescence spectra over a range of 800 − 2000 cm−1 with an approximately 100× increase in speed over prior RS Monte Carlo methods. The simulated RS signals are compared against experimentally collected spectra from gelatin phantoms, showing a strong correlation.image
Keywords:GPU  Monte Carlo method  parallel computing  Raman spectroscopy
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