QUT ePrints

Radiotherapy Monte Carlo simulation using cloud computing technology

Poole, Christopher, Cornelius, Iwan, Trapp, Jamie, & Langton, Christian M. (2012) Radiotherapy Monte Carlo simulation using cloud computing technology. Australasian Physical and Engineering Sciences in Medicine, 35(4), pp. 497-502.

View at publisher

Abstract

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.

Funding source Cancer Australia (Department of Health and Ageing) Research Grant 614217

Impact and interest:

1 citations in Scopus
Search Google Scholar™
1 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

20 since deposited on 19 Nov 2012
18 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 54848
Item Type: Journal Article
Additional Information: Additional information can be found at http://code.google.com/p/manysim/ If using this in a publication please cite this paper.
Additional URLs:
Keywords: cloud computing, Monte Carlo, GEANT4, radiotherapy
DOI: 10.1007/s13246-012-0167-8
ISSN: 1879-5447
Subjects: Australian and New Zealand Standard Research Classification > PHYSICAL SCIENCES (020000) > OTHER PHYSICAL SCIENCES (029900) > Medical Physics (029903)
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Australasian College of Physical Scientists and Engineers in Medicine
Copyright Statement: The final publication is available at www.springerlink.com
Deposited On: 19 Nov 2012 00:05
Last Modified: 30 Mar 2014 02:35

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page