Journal
JOURNAL OF BIOMEDICAL OPTICS
Volume 23, Issue 8, Pages -Publisher
SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JBO.23.8.085001
Keywords
Monte Carlo; photodynamic therapy; bioluminescence imaging; simulation; MCML; diffuse optical tomography
Funding
- Theralase Inc
- IBM
- Altera
- Canadian Natural Sciences and Engineering Research Council (NSERC/Altera Industrial Research Chair in Programmable Silicon)
- Canadian Institutes of Health Research (CGS-D)
- Ontario Centres of Excellence
- University of Toronto
Ask authors/readers for more resources
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. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available