Radiotherapy Monte Carlo simulation using cloud computing technology

被引:11
|
作者
Poole, C. M. [1 ,2 ,3 ]
Cornelius, I. [2 ,3 ]
Trapp, J. V. [2 ,3 ]
Langton, C. M. [2 ,3 ]
机构
[1] Royal Brisbane & Womens Hosp, Canc Care Serv, Herston, Qld 4029, Australia
[2] Queensland Univ Technol, Fac Sci & Technol, Discipline Phys, Brisbane, Qld 4000, Australia
[3] Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld 4000, Australia
关键词
Cloud computing; Monte Carlo; GEANT4; Radiotherapy; PLATFORM; TOOLKIT;
D O I
10.1007/s13246-012-0167-8
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1/n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal.
引用
收藏
页码:497 / 502
页数:6
相关论文
共 50 条
  • [1] Radiotherapy Monte Carlo simulation using cloud computing technology
    C. M. Poole
    I. Cornelius
    J. V. Trapp
    C. M. Langton
    Australasian Physical & Engineering Sciences in Medicine, 2012, 35 : 497 - 502
  • [2] GATE Monte Carlo simulation of dose distribution using MapReduce in a cloud computing environment
    Liu, Yangchuan
    Tang, Yuguo
    Gao, Xin
    AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE, 2017, 40 (04) : 777 - 783
  • [3] GATE Monte Carlo simulation of dose distribution using MapReduce in a cloud computing environment
    Yangchuan Liu
    Yuguo Tang
    Xin Gao
    Australasian Physical & Engineering Sciences in Medicine, 2017, 40 : 777 - 783
  • [4] Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce
    Pratx, Guillem
    Xing, Lei
    JOURNAL OF BIOMEDICAL OPTICS, 2011, 16 (12)
  • [5] Improving Parallelisation of a Monte Carlo Radiotherapy Simulation using MPI
    Yaikhom, Gagarine
    Walker, David W.
    Walker, Coral
    2012 IEEE 26TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS & PHD FORUM (IPDPSW), 2012, : 1033 - 1039
  • [6] GateCloud: An Integration of Gate Monte Carlo Simulation with A Cloud Computing Environment
    Rowedder, Blake A.
    Wang, Hui
    Kuang, Yu
    2014 IEEE 6TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM), 2014, : 433 - 438
  • [7] Monte Carlo simulation of dose distribution of radiotherapy
    Liu, YM
    Xue, DY
    Xu, XH
    Chen, Z
    System Simulation and Scientific Computing, Vols 1 and 2, Proceedings, 2005, : 422 - 426
  • [8] High-performance computing for Monte Carlo radiotherapy calculations
    Downes, P.
    Yaikhom, G.
    Giddy, J. P.
    Walker, D. W.
    Spezi, E.
    Lewis, D. G.
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2009, 367 (1897): : 2607 - 2617
  • [9] Evaluation of Highly Reliable Cloud Computing Systems using Non-Sequential Monte Carlo Simulation
    Snyder, B.
    Devabhaktuni, V.
    Alam, M.
    Green, Robert
    2014 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 2014, : 940 - 941
  • [10] Improving Cloud Simulation Using the Monte-Carlo Method
    Bertot, Luke
    Genaud, Stephane
    Gossa, Julien
    EURO-PAR 2018: PARALLEL PROCESSING, 2018, 11014 : 404 - 416