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Report on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

dc.contributor.authorArce, P.
dc.contributor.authorBolst, David
dc.contributor.authorBordage, M-C.
dc.contributor.authorBrown, J. M. C.
dc.contributor.authorCirrone, P.
dc.contributor.authorCortes-Giraldo, M. A.
dc.contributor.authorCutajar, D.
dc.contributor.authorCuttone, G.
dc.contributor.authorDesorgher, L.
dc.contributor.authorDondero, P.
dc.contributor.authorSimpson, Ed
dc.date.accessioned2022-02-06T23:07:29Z
dc.date.available2022-02-06T23:07:29Z
dc.date.issued2020
dc.date.updated2022-02-20T07:21:29Z
dc.description.abstractGeant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro‐ and nano‐ dosimetry, imaging, radiation protection and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. To respond to these needs, we developed G4‐Med, a benchmarking and regression testing system of Geant4 for medical physics, that currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the pre‐built, Geant4 physics lists are tested. The tests included in G4‐Med are executed on the CERN computing infrastructure via the use of the geant‐val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. This paper describes the tests included in G4‐Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.
dc.description.sponsorshipD. Bolst acknowledges the support of the Australian Government Research Training Program Scholarship. M. A. Cort ́es-Giraldo, A. Perales, and J. M. Quesada acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness under grant FPA2016-77689-C2-1-R. B. Faddegon and J. Ramos-M ́endez acknowledge partial financial support from the NIH grant U24CA215123. D. Bolst, S. Guatelli, D. Sakata, S.Incerti, and I. Kyriakou acknowledge financial support from the Australian Research Council, ARC DP170100967. S. Incerti acknowledges the financial support of CNRS through the IN2P3/MOVI Master Project and through the France-Greece PICS 8235 funding scheme. I. Kyriakou acknowledges additional financial support from the European Space Agency (Contract No. 4000126645/19/NL/BW). E. C. Simpson acknowledges financial support from the Australian Research Council under grant DP170102423. I. Sechopoulos and C. Fedon acknowledge financial support from the Susan G Komen Foundation for the Cure grant IIR13262248. S. Guatelli and D. Bolst acknowlege the use of computing resources of the Aus-tralian National Computing Infrastructure (NCI), through the NCMAS 2020 grant scheme.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn0971-6203en_AU
dc.identifier.urihttp://hdl.handle.net/1885/259083
dc.language.isoen_AUen_AU
dc.provenancehttps://v2.sherpa.ac.uk/id/publication/4194..."Author Accepted manuscript can be made open access on institutional repository with CC BY-NC-SA license" from SHERPA/RoMEO site (as at 7.2.2022).en_AU
dc.publisherMedknow Publications
dc.relationhttp://purl.org/au-research/grants/arc/DP170100967
dc.relationhttp://purl.org/au-research/grants/arc/DP170102423
dc.rights© 2020 American Association of Physicists in Medicine
dc.rights.licenseCreative Commons BY-NC-SAen_AU
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/en_AU
dc.sourceJournal of Medical Physics
dc.subjectbenchmarking
dc.subjectGeant4
dc.subjectmedical physics
dc.subjectMonte Carlo
dc.titleReport on G4‐Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group
dc.typeJournal article
dcterms.accessRightsOpen Accessen_AU
dcterms.dateAccepted2020-04-30
local.bibliographicCitation.issue1en_AU
local.bibliographicCitation.lastpage56en_AU
local.bibliographicCitation.startpage19en_AU
local.contributor.affiliationArce, P., CIEMATen_AU
local.contributor.affiliationBolst, David, University of Wollongongen_AU
local.contributor.affiliationBordage, M-C., Paul Sabatier Universityen_AU
local.contributor.affiliationBrown, J. M. C., Delft University of Technologyen_AU
local.contributor.affiliationCirrone, P., INFN LNSen_AU
local.contributor.affiliationCortes-Giraldo, M. A., Universidad de Sevillaen_AU
local.contributor.affiliationCutajar, D., University of Wollongongen_AU
local.contributor.affiliationCuttone, G., INFN LNSen_AU
local.contributor.affiliationDesorgher, L., Lausanne University Hospitalen_AU
local.contributor.affiliationDondero, P., SWHARDen_AU
local.contributor.affiliationSimpson, Ed, College of Science, ANUen_AU
local.contributor.authoruidSimpson, Ed, u5633413en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor111208 - Radiation Therapyen_AU
local.identifier.absfor020202 - Nuclear Physicsen_AU
local.identifier.absfor020201 - Atomic and Molecular Physicsen_AU
local.identifier.absseo970111 - Expanding Knowledge in the Medical and Health Sciencesen_AU
local.identifier.absseo970102 - Expanding Knowledge in the Physical Sciencesen_AU
local.identifier.ariespublicationU4474173xPUB67en_AU
local.identifier.citationvolume48en_AU
local.identifier.doi10.1002/mp.14226en_AU
local.identifier.scopusID2-s2.0-85097506923
local.publisher.urlhttps://aapm.onlinelibrary.wiley.com/en_AU
local.type.statusAccepted Versionen_AU

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