Efficient Monte Carlo simulations of spatially resolved reflectance for detection schemes with low numerical apertures

Yevhen Zelinskyi; Peter Naglič; Franjo Pernuš; Boštjan Likar; Miran Bürmen

doi:10.1117/12.2527044

11 July 2019 Efficient Monte Carlo simulations of spatially resolved reflectance for detection schemes with low numerical apertures

Yevhen Zelinskyi, Peter Naglič, Franjo Pernuš, Boštjan Likar, Miran Bürmen

Author Affiliations +

Proceedings Volume 11074, Diffuse Optical Spectroscopy and Imaging VII; 110741Y (2019) https://doi.org/10.1117/12.2527044
Event: European Conferences on Biomedical Optics, 2019, Munich, Germany

Abstract

Monte Carlo (MC) method is regarded as the gold standard for modeling the light transport in biological tissues. Due to the stochastic nature of the MC method, many photon packets need to be processed to obtain an adequate quality of the simulated reflectance. The number of required photon packets further increases if the numerical aperture of the detection scheme is low. Consequently, extensively long simulation times may be required to obtain adequate quality of the reflectance for such detection schemes. In this paper we propose an efficient regression model that maps reflectance simulated at the maximum acceptance angle of 90◦ to the reflectance corresponding to a much smaller realistic acceptance angle. The results of validation on spatially resolved reflectance and inverse models for estimation of optical properties show that the regression models are accurate and do not introduce additional errors into the spatially resolved reflectance or the optical properties estimated by appropriate inverse models from the regressed reflectance.

Citation Download Citation

Yevhen Zelinskyi, Peter Naglič, Franjo Pernuš, Boštjan Likar, and Miran Bürmen "Efficient Monte Carlo simulations of spatially resolved reflectance for detection schemes with low numerical apertures", Proc. SPIE 11074, Diffuse Optical Spectroscopy and Imaging VII, 110741Y (11 July 2019); https://doi.org/10.1117/12.2527044

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