An Efficiency Studying of an Ion Chamber Simulation Using Vriance Reduction Techniques with EGSnrc.

Clicks: 422
ID: 57311
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #1 of 6 articles by views in journal of biomedical physics & engineering

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Radiotherapy is an important technique of cancer treatment using ionizing radiation. The determination of total dose in reference conditions is an important contribution to uncertainty that could achieve 2%. The source of this uncertainty comes from cavity theory that relates the in-air cavity dose and the dose to water. These correction factors are determined from Monte Carlo calculations of ionization chambers. The main problem of this type of calculation is the extremely long computation time to achieve reasonable statistics.The main purpose of this work is to present a combination with variance reduction techniques for the case of an ionization chamber in water.The egs_chamber code allows for very efficient computation of ionization chamber doses and dose ratios by using various variance reduction techniques, and also permits realistic simulations of the experimental setup due to the use of EGSnrc C++ library. Russian roulette and Photon Cross Section Enhancement were used with egs_chamber code. Tests were performed to obtain the parameters of variance reduction techniques resulting in a maximum efficiency.It can be seen that the parameters which result in improved Monte Carlo calculation of the efficiency values are XCSE 64 and Russian Roulette (RR) 128.This study determines the parameters of variance reduction techniques that result in an optimal computational efficiency.
Reference Key
l-t2019anjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors L T, Campos;L A, Magalhães;C E V, de Almeida;
Journal journal of biomedical physics & engineering
Year 2019
DOI
10.22086/jbpe.v0i0.682
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.