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论文期刊

论文标题    Comparison of heuristic and deterministic algorithms in neutron coded imaging reconstruction
作者    Yan, Mingfei[1]; Hu, Huasi[1]; Hu, Guang[1];Liu, Zhihua[2]; He, Chao[3];Yi, Qiang[3]
发表/完成日期    2021-01-01
期刊名称    Nuclear Instruments and Methods in Physics Research, Section A
期卷    卷: 985
相关文章    1-s2.0-S0168900220311013-main_Comparison of heuristic and deterministic algorithms in neutron coded imaging reconstruction.pdf   
论文简介    摘要: Neutron coded imaging is an effective tool for diagnosing the shape, size and symmetry of deuterium (D)-tritium (T) plasma in inertial confinement fusion (ICF). It can provide an important reference for designing and improving the D-T pellet and confinement configuration. Image reconstruction algorithms play a role of reconstructing the source images from the blurred coded images and the point spread functions (PSFs) of imaging systems. Conventionally, the convolution model is used as the mathematical model for neutron coded imaging reconstruction, but it applies only to the spatially invariant PSF. In this paper, the linear equations model is regarded as the mathematical model for the reconstruction, and it can also be suitable for spatially variant PSF. In the reconstruction, the spatially variant PSFs were simulated through Monte Carlo method. Then an improved genetic algorithm (IGA) for the source image reconstruction was proposed. The comparison of its performance with other types of deterministic algorithms (like the algorithm with total variation (TV) minimization) was conducted, and the results showed that the IGA has better performance in source reconstruction regardless of the utilization of TV sparse prior. 关键词: 作者关键词:Fusion diagnosis; Neutron coded imaging; Monte Carlo simulation; Image reconstruction; Genetic algorithm; TV algorithm KeyWords Plus:FUSION 作者信息 通讯作者地址: Xi'an Jiaotong University Xi An Jiao Tong Univ, Sch Energy & Power Engn, Xian 710049, Peoples R China. 通讯作者地址: Hu, HS (通讯作者) 显示更多 Xi An Jiao Tong Univ, Sch Energy & Power Engn, Xian 710049, Peoples R China. 地址: [1]‎ Xi An Jiao Tong Univ, Sch Energy & Power Engn, Xian 710049, Peoples R China [2]‎ Univ Illinois, Dept Nucl Plasma & Radiol Engn, Champaign, IL 61820 USA [3]‎ China Acad Engn Phys, Inst Nucl Phys & Chem, Mianyang 621900, Sichuan, Peoples R China 电子邮件地址:huasi_hu@xjtu.edu.cn 基金资助致谢 基金资助机构显示详情 授权号 NSAF Joint Fund of China U1830128 National Natural Science Foundation of China (NSFC) 11975182,11875214 DOI: 10.1016/j.nima.2020.164704
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