Počet záznamů: 1
Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution
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SYSNO ASEP 0391473 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Estimating statistical uncertainty of Monte Carlo efficiency-gain in the context of a correlated sampling Monte Carlo code for brachytherapy treatment planning with non-normal dose distribution Tvůrce(i) Mukhopadhyay, N. D. (US)
Sampson, A. J. (US)
Deniz, D. (SE)
Carlsson, G. A. (SE)
Williamson, J. (US)
Malušek, Alexandr (UJF-V)Celkový počet autorů 6 Zdroj.dok. Applied Radiation and Isotopes. - : Elsevier - ISSN 0969-8043
Roč. 70, č. 1 (2012), s. 315-323Poč.str. 8 s. Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova Monte Carlo ; correlated sampling ; efficiency ; uncertainty ; bootstrap Vědní obor RIV BG - Jaderná, atomová a mol. fyzika, urychlovače CEZ AV0Z10480505 - UJF-V (2005-2011) UT WOS 000297901400052 DOI 10.1016/j.apradiso.2011.09.015 Anotace Correlated sampling Monte Carlo methods can shorten computing times in brachytherapy treatment planning. Monte Carlo efficiency is typically estimated via efficiency gain, defined as the reduction in computing time by correlated sampling relative to conventional Monte Carlo methods when equal statistical uncertainties have been achieved. The determination of the efficiency gain uncertainty arising from random effects, however, is not a straightforward task specially when the error distribution is non-normal. The purpose of this study is to evaluate the applicability of the F distribution and standardized uncertainty propagation methods (widely used in metrology to estimate uncertainty of physical measurements) for predicting confidence intervals about efficiency gain estimates derived from single Monte Carlo runs using fixed-collision correlated sampling in a simplified brachytherapy geometry. A bootstrap based algorithm was used to simulate the probability distribution of the efficiency gain estimates and the shortest 95% confidence interval was estimated from this distribution. It was found that the corresponding relative uncertainty was as large as 37% for this particular problem. The uncertainty propagation framework predicted confidence intervals reasonably well; however its main disadvantage was that uncertainties of input quantities had to be calculated in a separate run via a Monte Carlo method. The F distribution noticeably underestimated the confidence interval. These discrepancies were influenced by several photons with large statistical weights which made extremely large contributions to the scored absorbed dose difference. The mechanism of acquiring high statistical weights in the fixed-collision correlated sampling method was explained and a mitigation strategy was proposed. Pracoviště Ústav jaderné fyziky Kontakt Markéta Sommerová, sommerova@ujf.cas.cz, Tel.: 266 173 228 Rok sběru 2013 Elektronická adresa http://www.sciencedirect.com/science/article/pii/S0969804311004775
Počet záznamů: 1