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Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm

View ORCID ProfileYaoshen Yuan, View ORCID ProfileShijie Yan, View ORCID ProfileQianqian Fang
doi: https://doi.org/10.1101/2020.10.11.335232
Yaoshen Yuan
1Department of Electrical and Computer Engineering, Northeastern University, 360 Huntington Avenue Boston, MA 02115 US
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Shijie Yan
1Department of Electrical and Computer Engineering, Northeastern University, 360 Huntington Avenue Boston, MA 02115 US
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Qianqian Fang
2Department of Bioengineering, Northeastern University, 360 Huntington Avenue Boston, MA 02115 US
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  • For correspondence: q.fang@neu.edu
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Abstract

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • http://mcx.space/#mmc

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted October 12, 2020.
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Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm
Yaoshen Yuan, Shijie Yan, Qianqian Fang
bioRxiv 2020.10.11.335232; doi: https://doi.org/10.1101/2020.10.11.335232
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Light transport modeling in highly complex tissues using implicit mesh-based Monte Carlo algorithm
Yaoshen Yuan, Shijie Yan, Qianqian Fang
bioRxiv 2020.10.11.335232; doi: https://doi.org/10.1101/2020.10.11.335232

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