Denoising proton therapy Monte Carlo dose distributions in multiple tumor sites: A comparative neural networks architecture study
Abstract Introduction Monte Carlo (MC) algorithms provide accurate modeling of dose
calculation by simulating the delivery and interaction of many particles through patient …
calculation by simulating the delivery and interaction of many particles through patient …
Mitigating inherent noise in Monte Carlo dose distributions using dilated U‐Net
Purpose Monte Carlo (MC) algorithms offer accurate modeling of dose calculation by
simulating the transport and interactions of many particles through the patient geometry …
simulating the transport and interactions of many particles through the patient geometry …
A plan verification platform for online adaptive proton therapy using deep learning-based Monte–Carlo denoising
G Zhang, X Chen, J Dai, K Men - Physica Medica, 2022 - Elsevier
Abstract Background Purpose This study focused on developing a fast Monte Carlo (MC)
plan verification platform via a deep learning (DL)-based denoising approach. It can …
plan verification platform via a deep learning (DL)-based denoising approach. It can …
A novel multichannel deep learning model for fast denoising of Monte Carlo dose calculations: preclinical applications
RHW van Dijk, N Staut, CJA Wolfs… - Physics in Medicine & …, 2022 - iopscience.iop.org
Objective. In preclinical radiotherapy with kilovolt (kV) x-ray beams, accurate treatment
planning is needed to improve the translation potential to clinical trials. Monte Carlo based …
planning is needed to improve the translation potential to clinical trials. Monte Carlo based …
Deep learning‐based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy
X Zhang, H Zhang, J Wang, Y Ma, X Liu, Z Dai… - Medical …, 2023 - Wiley Online Library
Background Plan verification is one of the important steps of quality assurance (QA) in
carbon ion radiotherapy. Conventional methods of plan verification are based on phantom …
carbon ion radiotherapy. Conventional methods of plan verification are based on phantom …
Denoising Monte Carlo dose calculations using a deep neural network
H Fornander - 2019 - diva-portal.org
This thesis explores the possibility of using a deep neural network (DNN) to denoise Monte
Carlo dose calculations for external beam radiotherapy. The dose distributions considered …
Carlo dose calculations for external beam radiotherapy. The dose distributions considered …
High-particle simulation of monte-carlo dose distribution with 3D convlstms
Monte-Carlo simulation of radiotherapy dose remains an extremely time-consuming task,
despite being still the most precise tool for radiation transport calculation. To circumvent this …
despite being still the most precise tool for radiation transport calculation. To circumvent this …
Validation of a deep learning-based material estimation model for Monte Carlo dose calculation in proton therapy
Objective. Computed tomography (CT) to material property conversion dominates proton
range uncertainty, impacting the quality of proton treatment planning. Physics-based and …
range uncertainty, impacting the quality of proton treatment planning. Physics-based and …
Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy
O Pastor-Serrano, Z Perkó - Physics in Medicine & Biology, 2022 - iopscience.iop.org
Objective. Next generation online and real-time adaptive radiotherapy workflows require
precise particle transport simulations in sub-second times, which is unfeasible with current …
precise particle transport simulations in sub-second times, which is unfeasible with current …
Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation
Background In proton therapy dose calculation, Monte Carlo (MC) simulations are superior
in accuracy but more time consuming, compared to analytical calculations. Graphic …
in accuracy but more time consuming, compared to analytical calculations. Graphic …