ARI-MA: Development of Integrated Real-Time Imaging and Isotope Detection Algorithms for 3-D Position-Sensitive Semiconductor Gamma-Ray Imaging Spectrometers and Sensor Networks

ARI-MA：开发用于 3D 位置敏感半导体伽马射线成像光谱仪和传感器网络的集成实时成像和同位素检测算法

• 批准号: 0736091
• 负责人: Zhong He
• 金额: $ 37.78万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0736091&HistoricalAwards=false
• 关键词: ARI; MA; Development; Integrated; Real

0736091HeThe team will conduct research on fast image reconstruction using two novel convergent maximum-likelihood (ML) reconstruction methods employing iterative algorithms based upon ordered-subsets principles. These algorithms, unlike others, are guaranteed to converge regardless of the presence of noise, and regardless of whether any subset balance conditions are met. They will investigate techniques for detecting the change of recorded gamma rays in spatial, spectral, and timing domains. The energy spectra will then be analyzed in order to identify the specific isotope, by using wavelet analysis, feature extraction and reconstruction, and pattern recognition to compare theoretical (from a library) and measured patterns. The specific isotope will then be identified by a decision-making strategy. The project will make contributions to science and knowledge in radiation detection, signal processing, identification, and locating of highly enriched uranium, plutonium, and other radioactive isotopes that might be used for "dirty bombs".

0736091He该团队将使用两种新的收敛最大似然（ML）重建方法进行快速图像重建研究，该方法采用基于有序子集原理的迭代算法。与其他算法不同，这些算法保证收敛，而不管是否存在噪声，也不管是否满足任何子集平衡条件。他们将研究在空间，光谱和时间域中检测记录的伽马射线变化的技术。然后将分析能谱，以便通过使用小波分析、特征提取和重建以及模式识别来比较理论模式（来自库）和测量模式，从而识别特定同位素。然后将通过决策策略确定具体的同位素。 该项目将为辐射探测、信号处理、识别和定位可能用于“脏弹”的高浓缩铀、钚和其他放射性同位素方面的科学和知识作出贡献。