CALCULATION OF THE ABSORBED DOSE IN PHANTOMS USING THE DOSXYZNRC SOFTWARE PACKAGE
, 2023 Based directly on the DOSXYZ code created for the EGS4 code system, DOSXYZnrc is a Monte Carlo simulation code for determining dose distributions in a rectilinear voxel phantom. The OMEGA-BEAM system of codes created at NRC includes DOSXYZnrc. Every voxel may have a different density and substance.
Ashurov Sindorjon Akhmadjon ugli, Yomghirov Olimjon Tolib ugli, Karimova Nozliya Nabijon qiz
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Wahana Fisika: Jurnal Penelitian Fisika dan Terapannya, 2016 Telah dilakukan penelitian tentang perbandingan dosis serap berkas foton 16 MV pada berbagai jenis material phantom dengan menggunakan simulasi Monte Carlo-EGSnrc.
Ridwan Ramdani, Freddy Haryanto
doaj +4 more sources
Development and Validation of a Monte Carlo Beam Model for 6, 8, and 15 MV Clinical Photon Beams on the Elekta™ Precise Linac [PDF]
Journal of Medical PhysicsIntroduction: This study investigates a single-source photon beam model and a single source for contamination electrons for Monte Carlo (MC) simulations.
JJL Smit +2 more
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Evaluation of MLC Thickness and Composite Effects on Collimation Parameters using EGSnrc and IAEA Phase Space Data [PDF]
Journal of Biomedical Physics and Engineering, 2020 Background: Recently, multileaf collimators (MLC) have become an important part of any LINAC collimation system because they reduce the treatment planning time and improve the conformity.
K Hadad, H Alipour
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Improving animal-specific radiotherapy quality assurance for kilovoltage X-ray radiotherapy using a 3D printed dog skull water phantom [PDF]
Open Veterinary Journal, 2023 Background: Accurate dose assessment during animal radiotherapy is beneficial for veterinary medicine and medical education. Aim: To visualize the radiation treatment distribution of orthovoltage X-ray equipment in clinical practice using Monte Carlo ...
Yoshinori Tanabe +5 more
doaj +2 more sources
Design and validation of a deep learning GAN for predicting <sup>1</sup> <sup>7</sup> <sup>7</sup>Lu dose voxel kernels using GATE/GEANT4 Monte Carlo and IDAC-Dose 2.1 in phantom dosimetry. [PDF]
J Appl Clin Med PhysAbstract Background The rapid evolution of deep learning (DL), particularly the emergence of generative adversarial networks (GANs) has demonstrated strong potential for generating high‐resolution, voxel‐level dosimetric data. However, GAN‐based approaches have not yet been broadly applied to the generation of tissue‐specific dose voxel kernels (DVKs ...
Kapis OE +3 more
europepmc +2 more sources
An Approach in Radiation Therapy Treatment Planning: A Fast, GPU-Based Monte Carlo Method
Journal of Medical Signals and Sensors, 2017 An accurate and fast radiation dose calculation is essential for successful radiation radiotherapy. The aim of this study was to implement a new graphic processing unit (GPU) based radiation therapy treatment planning for accurate and fast dose ...
Mojtaba Karbalaee +2 more
doaj +1 more source
The dosimetric effect of photon target degradation on C-series linear accelerators using Monte Carlo simulation. [PDF]
J Appl Clin Med PhysAbstract Background The impact of beam dosimetry changes brought on by target degradation has not been well investigated. Purpose To determine the optimal dosimetry metrics for detecting target degradation and to investigate the impact of beam dosimetry changes brought on by target degradation. Methods The EGSnrc Monte Carlo programs were used to model
Deng Y, Qiu M, Zhong J, Xiao Z.
europepmc +2 more sources
A comparison of the JO-IMRT dose distribution calculated by the SOURCE 8 and 20 in the DOSXYZnrc for head-and-neck cancer [PDF]
International Journal of Radiation Research, 2021 Tuan Hoang
exaly +2 more sources
Monte Carlo modeling of radiation dose from radiation therapy with superficial x-rays. [PDF]
J Appl Clin Med PhysAbstract Introduction Superficial x‐rays (50–100 kVp) are used for treating non‐melanoma skin cancer and intraoperative radiation therapy (IORT). At these energies, the photoelectric effect significantly increases absorbed dose to bone compared to soft tissue.
Barghash R +3 more
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