TY - JOUR
T1 - The adaptation method in the Monte Carlo simulation for computed tomography
AU - Lee, Hyounggun
AU - Yoon, Changyeon
AU - Cho, Seungryong
AU - Park, Sung Ho
AU - Lee, Wonho
N1 - Funding Information:
This work was supported by a National Research Foundation of Korea (NRF) ( 2011-0031464 and 2012-0006399 ) grant and BK21PLUS funded by the Ministry of Science and Education (MEST) of the Korean government (grant numbers, 2011-0031464 , 2012-0006399 ).
Publisher Copyright:
© 2015, Published by Elsevier Korea LLC on behalf of Korean Nuclear Society.
PY - 2015
Y1 - 2015
N2 - The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterationsdassuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
AB - The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterationsdassuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.
KW - Adaptive method
KW - Deterministic method
KW - Monte Carlo simulation
UR - http://www.scopus.com/inward/record.url?scp=84931086454&partnerID=8YFLogxK
U2 - 10.1016/j.net.2015.01.010
DO - 10.1016/j.net.2015.01.010
M3 - Article
AN - SCOPUS:84931086454
SN - 1738-5733
VL - 47
SP - 472
EP - 478
JO - Nuclear Engineering and Technology
JF - Nuclear Engineering and Technology
IS - 4
ER -