Literature DB >> 31565520

FullMonteCUDA: a fast, flexible, and accurate GPU-accelerated Monte Carlo simulator for light propagation in turbid media.

Tanner Young-Schultz1, Stephen Brown1, Lothar Lilge2,3, Vaughn Betz1.   

Abstract

Optimizing light delivery for photodynamic therapy, quantifying tissue optical properties or reconstructing 3D distributions of sources in bioluminescence imaging and absorbers in diffuse optical imaging all involve solving an inverse problem. This can require thousands of forward light propagation simulations to determine the parameters to optimize treatment, image tissue or quantify tissue optical properties, which is time-consuming and computationally expensive. Addressing this problem requires a light propagation simulator that produces results quickly given modelling parameters. In previous work, we developed FullMonteSW: currently the fastest, tetrahedral-mesh, Monte Carlo light propagation simulator written in software. Additional software optimizations showed diminishing performance improvements, so we investigated hardware acceleration methods. This work focuses on FullMonteCUDA: a GPU-accelerated version of FullMonteSW which targets NVIDIA GPUs. FullMonteCUDA has been validated across several benchmark models and, through various GPU-specific optimizations, achieves a 288-936x speedup over the single-threaded, non-vectorized version of FullMonteSW and a 4-13x speedup over the highly optimized, hand-vectorized and multi-threaded version. The increase in performance allows inverse problems to be solved more efficiently and effectively.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.

Year:  2019        PMID: 31565520      PMCID: PMC6757465          DOI: 10.1364/BOE.10.004711

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  34 in total

1.  Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range.

Authors:  A N Yaroslavsky; P C Schulze; I V Yaroslavsky; R Schober; F Ulrich; H J Schwarzmaier
Journal:  Phys Med Biol       Date:  2002-06-21       Impact factor: 3.609

2.  In vivo local determination of tissue optical properties: applications to human brain.

Authors:  F Bevilacqua; D Piguet; P Marquet; J D Gross; B J Tromberg; C Depeursinge
Journal:  Appl Opt       Date:  1999-08-01       Impact factor: 1.980

3.  Hardware acceleration of a Monte Carlo simulation for photodynamic therapy [corrected] treatment planning.

Authors:  William Chun Yip Lo; Keith Redmond; Jason Luu; Paul Chow; Jonathan Rose; Lothar Lilge
Journal:  J Biomed Opt       Date:  2009 Jan-Feb       Impact factor: 3.170

4.  Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration.

Authors:  Erik Alerstam; Tomas Svensson; Stefan Andersson-Engels
Journal:  J Biomed Opt       Date:  2008 Nov-Dec       Impact factor: 3.170

5.  Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties.

Authors:  Vinh Nguyen Du Le; John Provias; Naresh Murty; Michael S Patterson; Zhaojun Nie; Joseph E Hayward; Thomas J Farrell; William McMillan; Wenbin Zhang; Qiyin Fang
Journal:  J Biomed Opt       Date:  2017-02-01       Impact factor: 3.170

6.  Parallelized Monte-Carlo dosimetry using graphics processing units to model cylindrical diffusers used in photodynamic therapy: From implementation to validation.

Authors:  Clément Dupont; Gregory Baert; Serge Mordon; Maximilien Vermandel
Journal:  Photodiagnosis Photodyn Ther       Date:  2019-04-27       Impact factor: 3.631

7.  Automatic interstitial photodynamic therapy planning via convex optimization.

Authors:  Abdul-Amir Yassine; William Kingsford; Yiwen Xu; Jeffrey Cassidy; Lothar Lilge; Vaughn Betz
Journal:  Biomed Opt Express       Date:  2018-01-30       Impact factor: 3.732

8.  Next-generation acceleration and code optimization for light transport in turbid media using GPUs.

Authors:  Erik Alerstam; William Chun Yip Lo; Tianyi David Han; Jonathan Rose; Stefan Andersson-Engels; Lothar Lilge
Journal:  Biomed Opt Express       Date:  2010-08-23       Impact factor: 3.732

9.  Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates.

Authors:  Qianqian Fang
Journal:  Biomed Opt Express       Date:  2010-07-15       Impact factor: 3.732

10.  Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms.

Authors:  Leiming Yu; Fanny Nina-Paravecino; David Kaeli; Qianqian Fang
Journal:  J Biomed Opt       Date:  2018-01       Impact factor: 3.170

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  12 in total

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

Authors:  Yaoshen Yuan; Shijie Yan; Qianqian Fang
Journal:  Biomed Opt Express       Date:  2020-12-08       Impact factor: 3.732

2.  Hybrid mesh and voxel based Monte Carlo algorithm for accurate and efficient photon transport modeling in complex bio-tissues.

Authors:  Shijie Yan; Qianqian Fang
Journal:  Biomed Opt Express       Date:  2020-10-08       Impact factor: 3.732

3.  Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.

Authors:  Shoujing Guo; Jin U Kang
Journal:  Opt Express       Date:  2022-07-04       Impact factor: 3.833

4.  BlenderPhotonics: an integrated open-source software environment for three-dimensional meshing and photon simulations in complex tissues.

Authors:  Yuxuang Zhang; Qianqian Fang
Journal:  J Biomed Opt       Date:  2022-04       Impact factor: 3.758

5.  MCDataset: a public reference dataset of Monte Carlo simulated quantities for multilayered and voxelated tissues computed by massively parallel PyXOpto Python package.

Authors:  Miran Bürmen; Franjo Pernuš; Peter Naglič
Journal:  J Biomed Opt       Date:  2022-04       Impact factor: 3.758

6.  Modeling voxel-based Monte Carlo light transport with curved and oblique boundary surfaces.

Authors:  Anh Phong Tran; Steven Jacques
Journal:  J Biomed Opt       Date:  2020-02       Impact factor: 3.170

7.  Review of in vivo optical molecular imaging and sensing from x-ray excitation.

Authors:  Brian W Pogue; Rongxiao Zhang; Xu Cao; Jeremy Mengyu Jia; Arthur Petusseau; Petr Bruza; Sergei A Vinogradov
Journal:  J Biomed Opt       Date:  2021-01       Impact factor: 3.170

8.  MCX Cloud-a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing.

Authors:  Qianqian Fang; Shijie Yan
Journal:  J Biomed Opt       Date:  2022-01       Impact factor: 3.170

9.  Scalable and accessible personalized photodynamic therapy optimization with FullMonte and PDT-SPACE.

Authors:  Shuran Wang; Xiao Ying Dai; Shengxiang Ji; Tina Saeidi; Fynn Schwiegelshohn; Abdul-Amir Yassine; Lothar Lilge; Vaughn Betz
Journal:  J Biomed Opt       Date:  2022-04       Impact factor: 3.758

10.  Modeling the efficiency of UV at 254 nm for disinfecting the different layers within N95 respirators.

Authors:  Abdallatif Satti Abdalrhman; Chengjin Wang; Angelica Manalac; Madrigal Weersink; Abdul-Amir Yassine; Vaughn Betz; Benoit Barbeau; Lothar Lilge; Ron Hofmann
Journal:  J Biophotonics       Date:  2021-07-11       Impact factor: 3.390

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