Open Access
10 August 2018 High-performance, robustly verified Monte Carlo simulation with FullMonte
Jeffrey Cassidy, Ali Nouri, Vaughn Betz, Lothar Lilge
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Abstract
We introduce the FullMonte tetrahedral 3-D Monte Carlo (MC) software package for simulation, visualization, and analysis of light propagation in heterogeneous turbid media including tissue. It provides the highest computational performance and richest set of input, output, and analysis facilities of any open-source tetrahedral-mesh MC light simulator. It also provides a robust framework for statistical verification. A scripting interface makes set-up of simulation runs simple, including parameter sweeps, while simultaneously providing customization options. Data formats shared with class-leading visualization tools, VTK and Paraview, facilitate interactive generation of publication-quality fluence and irradiance maps. The simulator can read and write file formats supported by other similar simulators, such as TIM-OS, MMC, COMSOL (finite-element simulations), and MCML to support comparison. Where simulator features permit, FullMonte can take a single test case, run it in multiple software packages, and load the results together for comparison. Example meshes, optical properties, set-up scripts, and output files are provided for user convenience. We demonstrate its use in several test cases, including photodynamic therapy of the brain, bioluminescence imaging (BLI) in a mouse phantom, and a comparison against MCML for layered geometries. Application domains that can benefit from use of FullMonte include photodynamic, photothermal, and photobiomodulation therapies, BLI, diffuse optical tomography, MC software development, and biophotonics education. Since MC results may be used for preclinical or even clinical experiments, a robust and rigorous verification process is essential. Being a stochastic numerical method, MC simulation has unique challenges associated with verification of output results since observed differences may be due simply to output variance or actual differences in expected output. We describe and have implemented a rigorous and statistically justified framework for comparing between simulators of the same class and for performing regression testing.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Jeffrey Cassidy, Ali Nouri, Vaughn Betz, and Lothar Lilge "High-performance, robustly verified Monte Carlo simulation with FullMonte," Journal of Biomedical Optics 23(8), 085001 (10 August 2018). https://doi.org/10.1117/1.JBO.23.8.085001
Received: 9 April 2018; Accepted: 10 July 2018; Published: 10 August 2018
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CITATIONS
Cited by 50 scholarly publications.
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KEYWORDS
Monte Carlo methods

Visualization

Absorption

Optical properties

Computer simulations

Photodynamic therapy

Statistical analysis

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