Literature DB >> 19256707

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

William Chun Yip Lo1, Keith Redmond, Jason Luu, Paul Chow, Jonathan Rose, Lothar Lilge.   

Abstract

Monte Carlo (MC) simulations are being used extensively in the field of medical biophysics, particularly for modeling light propagation in tissues. The high computation time for MC limits its use to solving only the forward solutions for a given source geometry, emission profile, and optical interaction coefficients of the tissue. However, applications such as photodynamic therapy treatment planning or image reconstruction in diffuse optical tomography require solving the inverse problem given a desired dose distribution or absorber distribution, respectively. A faster means for performing MC simulations would enable the use of MC-based models for accomplishing such tasks. To explore this possibility, a digital hardware implementation of a MC simulation based on the Monte Carlo for Multi-Layered media (MCML) software was implemented on a development platform with multiple field-programmable gate arrays (FPGAs). The hardware performed the MC simulation on average 80 times faster and was 45 times more energy efficient than the MCML software executed on a 3-GHz Intel Xeon processor. The resulting isofluence lines closely matched those produced by MCML in software, diverging by only less than 0.1 mm for fluence levels as low as 0.00001 cm(-2) in a skin model.

Entities:  

Mesh:

Year:  2009        PMID: 19256707     DOI: 10.1117/1.3080134

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  7 in total

1.  Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce.

Authors:  Guillem Pratx; Lei Xing
Journal:  J Biomed Opt       Date:  2011-12       Impact factor: 3.170

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

Authors:  Tanner Young-Schultz; Stephen Brown; Lothar Lilge; Vaughn Betz
Journal:  Biomed Opt Express       Date:  2019-08-21       Impact factor: 3.732

3.  Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units.

Authors:  Qianqian Fang; David A Boas
Journal:  Opt Express       Date:  2009-10-26       Impact factor: 3.894

4.  A tetrahedron-based inhomogeneous Monte Carlo optical simulator.

Authors:  H Shen; G Wang
Journal:  Phys Med Biol       Date:  2010-01-20       Impact factor: 3.609

5.  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

6.  GPU-accelerated Monte Carlo simulation of MV-CBCT.

Authors:  Mengying Shi; Marios Myronakis; Matthew Jacobson; Dianne Ferguson; Christopher Williams; Mathias Lehmann; Paul Baturin; Pascal Huber; Rony Fueglistaller; Ingrid Valencia Lozano; Thomas Harris; Daniel Morf; Ross I Berbeco
Journal:  Phys Med Biol       Date:  2020-12-02       Impact factor: 4.174

7.  Efficient inversion strategies for estimating optical properties with Monte Carlo radiative transport models.

Authors:  Callum Macdonald; Simon Arridge; Samuel Powell
Journal:  J Biomed Opt       Date:  2020-08       Impact factor: 3.170

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.