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Experimental setup geometry in Monte Carlo (MC) simulations is often simplified to shorten computation times. We investigate the effect of these simplifications on the accuracy of the spatial frequency domain (SFD) reflectance. We also introduce a new detection scheme in the MC method that eliminates the often overlooked errors arising from the Hankel transform of the spatially discretized reflectance profiles to SFD reflectance. Finally, we propose and evaluate an artificial neural network-based framework capable of estimating high-definition maps of optical properties in real-time.
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Peter Naglič, Yevhen Zelinskyi, Boštjan Likar, Franjo Pernuš, Miran Bürmen, "From Monte Carlo simulations to efficient estimation of optical properties for spatial frequency domain imaging," Proc. SPIE 10862, Molecular-Guided Surgery: Molecules, Devices, and Applications V, 1086209 (7 March 2019); https://doi.org/10.1117/12.2510195