Accelerating 3-D Monte Carlo Photon Transport Simulations by Leveraging Deep-learning based Volume Super-Resolution Methods

We present a deep-learning approach to upscale Monte Carlo (MC) simulations for modeling light propagation inside turbid media, surpassing traditional algorithms by offering up to about 4 times additional photons compared to direct MC simulations.