A multivariate approach to determine electron beam parameters for a Monte Carlo 6 MV Linac model: Statistical and machine learning methods-Reference-Cited by-同舟云学术

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A multivariate approach to determine electron beam parameters for a Monte Carlo 6 MV Linac model: Statistical and machine learning methods

Published:2022-01 Issue: Volume:93 Page:38-45
ISSN:1120-1797
Container-title:Physica Medica
language:en
Short-container-title:Physica Medica

Author:

Yang Hye Jeong,Kim Tae Hoon,Schaarschmidt Thomas,Park Dong-Wook,Kang Seung Hee,Chung Hyun-Tai,Suh Tae Suk

Funder

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

Publisher

Elsevier BV

Subject

General Physics and Astronomy,Radiology, Nuclear Medicine and imaging,General Medicine,Biophysics

Reference30 articles.

1. Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157;Ma;Med Phys,2020

2. Monte Carlo modeling of external photon beams in radiotherapy;Verhaegen;Phys Med Biol,2003

3. Efficiency improvements of X-ray simulations in EGSnrc user-codes using bremsstrahlung cross-section enhancement (BCSE);Ali;Med Phys,2007

4. Linac photon beam fine-tuning in PRIMO using the gamma-index analysis toolkit;Bacala;Radiat Oncol,2020

5. Validation of Monte Carlo Geant4 code for a 6 MV Varian linac;El Bakkali;J King Saud University - Science,2017

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1. Machine learning and neural networks based approach for deflection prediction of Euler-Bernoulli beam equations;Mathematica Montisnigri;2023

2. Developing a new Monte Carlo algorithm as an alternative tool to simulate virtual source model on an Elekta Versa HD Linac;Journal of Radiation Research and Applied Sciences;2022-09

3. Developing a New Monte Carlo Algorithm as an Alternative Tool to Simulate Virtual Source Model on an Elekta Versa Hd Linac;2022-08-19

4. Measurement of linear accelerator spectra, reconstructed from percentage depth dose curves by neural networks;Physica Medica;2022-04

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