The regional Monte Carlo method: A dose calculation method based on accuracy requirement

1998 ◽  
Vol 25 (10) ◽  
pp. 1866-1871 ◽  
Author(s):  
M. K. Woo ◽  
D. J. Scora ◽  
E. Wong
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Calculation Method ◽  
Dose Calculation ◽  
Accuracy Requirement

Experimental verification of dose calculation using the simplified Monte Carlo method with an improved initial beam model for a beam-wobbling system

2013 ◽  
Vol 58 (17) ◽  
pp. 6047-6064 ◽  
Author(s):  
Ryohei Tansho ◽  
Yoshihisa Takada ◽  
Ryosuke Kohno ◽  
Kenji Hotta ◽  
Yousuke Hara ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Experimental Verification ◽  
Dose Calculation ◽  
Beam Model ◽  
Initial Beam

Computing Profiles of Porosity and Surface/Volume Ratio in a Packed Bed Using Monte Carlo Method

2013 ◽  
Author(s):  
Genong Li
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Particle Diameter ◽  
Volume Ratio ◽  
Packed Bed ◽  
Diameter Ratio ◽  
Accuracy Requirement ◽  
Radial Profiles ◽  
Novel Method ◽  
Rigorous Error

Porosity and surface/volume ratio are two important parameters for a packed bed. In cylindrical packed beds at low tube-to-particle diameter ratio, they vary greatly in the radial direction. In the existing literature, radial profiles of porosity and surface/volume ratio have been computed using some analytical equations which involve elliptic integrals. In this paper, a Monte Carlo method is used to compute those profiles. To the authors’ knowledge, the method has never been employed in this context. The procedure of using this novel method is explained in detail. Through a rigorous error analysis based on statistics, the accuracy of the simulation result can be controlled. Before any simulation, the number of sampling points needed in the Monte Carlo simulation can be determined given an accuracy requirement. The method is completely general and can be used to compute profiles of porosity and surface/volume ratio in any packed bed with any shape of packing elements.

SU-GG-T-424: Domain-Division Monte Carlo Dose Calculation Method for Particle Therapy

2010 ◽  
Vol 37 (6Part22) ◽  
pp. 3284-3284
Author(s):  
KL Ishikawa ◽  
K Niita ◽  
K Takeda ◽  
N Fukunishi ◽  
S Takagi
Keyword(s):  
Monte Carlo ◽  
Calculation Method ◽  
Dose Calculation ◽  
Particle Therapy ◽  
Monte Carlo Dose Calculation

SU-E-T-224: Is Monte Carlo Dose Calculation Method Necessary for Cyberknife Brain Treatment Planning?

2014 ◽  
Vol 41 (6Part14) ◽  
pp. 275-275
Author(s):  
L Wang ◽  
E Fourkal ◽  
S Hayes ◽  
L Jin ◽  
C Ma
Keyword(s):  
Monte Carlo ◽  
Treatment Planning ◽  
Calculation Method ◽  
Dose Calculation ◽  
Monte Carlo Dose Calculation

A patient-specific Monte Carlo dose-calculation method for photon beams

1998 ◽  
Vol 25 (6) ◽  
pp. 867-878 ◽  
Author(s):  
Lu Wang ◽  
Chen-Shou Chui ◽  
Michael Lovelock
Keyword(s):  
Monte Carlo ◽  
Calculation Method ◽  
Dose Calculation ◽  
Patient Specific ◽  
Photon Beams ◽  
Monte Carlo Dose Calculation

scholarly journals The simulation of a linear accelerator using Monte Carlo method with EGSnrc Program

2019 ◽  
Vol 2 (4) ◽  
pp. 103-111
Author(s):  
Tai Thanh Duong ◽  
Tuan Duc Hoang ◽  
Oanh Thi Luong ◽  
Loan Thi Hong Truong ◽  
Son Dong Nguyen
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Excellent Agreement ◽  
Linear Accelerator ◽  
Evaluation Method ◽  
Dose Calculation ◽  
Calculation Algorithm ◽  
Simulation Accuracy ◽  
Depth Dose ◽  
Passing Rate

The Monte Carlo method is considered to be the most accurate algorithm for dose calculation in radiotherapy. Linear accelerator accurate simulation is required as a prior condition for Monte Carlo dose calculation algorithm. In this study, the 6 MV photon beams from a Siemens Primus Linear Accelerator (LINAC) M5497 at the Dong Nai General Hospital was modelled by using EGSnrc. The BEAMnrc và DOSXYZnrc user code were used for simulation the head of LINAC and the dose distribution in water phantom. The percentage depth dose (PDD) and beam profiles (OCR) were calculated and then compared with the measured ones in order to evaluate the simulation accuracy. Excellent agreement was found between simulations and measurements with an average difference of 1.26 % for PDD, less than 2 % for OCR. In addition, the gamma evaluation method for simulation was also performed using an in-house Matlab code. The percentage gamma passing rate was 100% for PDD and 98.5 % for OCR with 3 % dose difference and 3 mm distance to agreement as acceptance criteria. The result showed that we had successfully simulated LINAC with excellent agreement.

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