GPU-Accelerated Monte Carlo Raman Spectroscopy Simulation: Unlocking Computational Speed for Cancer Detection Skip to main content
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2024 Abstracts

GPU-Accelerated Monte Carlo Raman Spectroscopy Simulation: Unlocking Computational Speed for Cancer Detection

Authors: Thomas Caldwell
Mentors: Dustin Shipp
Insitution: Utah Valley University

In this research project, we have transformed an existing Raman spectroscopy simulation, enhancing its performance and capabilities through the integration of parallel computing with GPU acceleration. This significant improvement in computation time allows us to break through previous computational limitations, enabling more sophisticated and complex applications of the simulation. The principal applications we will be assessing are the viability and potential of spatially offset Raman spectroscopy (SORS) for deeper tissue analysis, exploring the possibilities of topographical imaging using Raman techniques, and the advanced application of chemical imaging of microscopic tumors. This expanded scope demonstrates the simulation's potential in early cancer detection.