迭代重建
稳健性(进化)
μ介子
算法
断层摄影术
断层重建
宇宙射线
计算机科学
散射
重建算法
物理
期望最大化算法
氡变换
人工智能
计算机视觉
光学
数学
最大似然
统计
核物理学
生物化学
化学
基因
作者
Larry J. Schultz,Gary Blanpied,K. Borozdin,Andrew M. Fraser,Nicolas Hengartner,A. Klimenko,C. L. Morris,Chris Orum,Michael James Sossong
标识
DOI:10.1109/tip.2007.901239
摘要
Highly penetrating cosmic ray muons constantly shower the earth at a rate of about 1 muon per cm2 per minute. We have developed a technique which exploits the multiple Coulomb scattering of these particles to perform nondestructive inspection without the use of artificial radiation. In prior work [1]-[3], we have described heuristic methods for processing muon data to create reconstructed images. In this paper, we present a maximum likelihood/expectation maximization tomographic reconstruction algorithm designed for the technique. This algorithm borrows much from techniques used in medical imaging, particularly emission tomography, but the statistics of muon scattering dictates differences. We describe the statistical model for multiple scattering, derive the reconstruction algorithm, and present simulated examples. We also propose methods to improve the robustness of the algorithm to experimental errors and events departing from the statistical model.
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