Author:
Zhu Tengfei,Liu Yang,Luo Zhi,Ouyang Xiaoping
Abstract
Abstract
The low intensity of the neutron source for neutron computed tomography (CT) results in a long acquisition time for a single projection, which causes the neutron projection data to contain a large amount of quantum noise. Quantum noise will degrade the quality of neutron CT reconstruction images. Therefore, an efficient quantum noise removal algorithm must be used in CT reconstruction. In this paper, an efficient quantum noise removal algorithm for neutron CT 3D image reconstruction is proposed by analysing classical image processing algorithms and quantum image processing algorithms, which employs the maximum likelihood expectation maximization to reconstruct the image and split Bregman algorithm to solve for the total variation (MLEM-SBTV). Experimental results show that MLEM-SBTV performs well in removing quantum noise and reconstructing the detailed structure of images.
Funder
Joint Innovation Fund of China National Uranium Co., Ltd., State Key Laboratory of Nuclear Resources and Environment, East China University of Technology
Joint Fund of Ministry of Education for Equipment Pre-research
Fundamental Research Funds for the Central Universities
Fund of Innovation Center of Radiation Application
National Key Research and Development Program of China
National Natural Science Foundation of China
Fund of the State Key Laboratory of Nuclear Physics and Technology, Peking University
Fund of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect
Cited by
1 articles.
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