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High performance gamma-ray imager using dual anti-mask method for the investigation of high-energy nuclear materials

Authors
Lee, TaewoongLee, Wonho
Issue Date
7월-2021
Publisher
KOREAN NUCLEAR SOC
Keywords
Dual anti-mask method; Hybrid update maximum likelihood; expectation maximization (h-MLEM)
Citation
NUCLEAR ENGINEERING AND TECHNOLOGY, v.53, no.7, pp.2371 - 2376
Indexed
SCIE
SCOPUS
KCI
Journal Title
NUCLEAR ENGINEERING AND TECHNOLOGY
Volume
53
Number
7
Start Page
2371
End Page
2376
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/127766
DOI
10.1016/j.net.2021.01.027
ISSN
1738-5733
Abstract
As the gamma-ray energy increases, a reconstructed image becomes noisy and blurred due to the penetration of the gamma-ray through the coded mask. Therefore, the thickness of the coded mask was increased for high energy regions, resulting in severely decreased the performance of the detection efficiency due to self collimation by the mask. In order to overcome the limitation, a modified uniformly redundant array y ray imaging system using dual anti-mask method was developed, and its performance was compared and evaluated in high-energy radiation region. In the dual anti-mask method, the two shadow images, including the subtraction of background events, can simultaneously contribute to the reconstructed image. Moreover, the reconstructed images using each shadow image were integrated using a hybrid update maximum likelihood expectation maximization (h-MLEM). Using the quantitative evaluation method, the performance of the dual anti-mask method was compared with the previously developed collimation methods. As the shadow image which was subtracted the background events leads to a higher-quality reconstructed image, the reconstructed image of the dual anti-mask method showed high performance among the three collimation methods. Finally, the quantitative evaluation method proves that the performance of the dual anti-mask method was better than that of the previously reconstruction methods. (C) 2021 Korean Nuclear Society, Published by Elsevier Korea LLC.
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Lee, Won ho
보건과학대학 (보건환경융합과학부)
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