Suppr超能文献

基于X射线计算机断层扫描的有机材料识别多能量快速收敛迭代重建算法

Multi-Energy and Fast-Convergence Iterative Reconstruction Algorithm for Organic Material Identification Using X-ray Computed Tomography.

作者信息

Iovea Mihai, Stanciulescu Andrei, Hermann Edward, Neagu Marian, Duliu Octavian G

机构信息

Accent Pro 2000 srl, 25A, Mărășești Str., 077125 Magurele (Ilfov), Romania.

Department of Structure of Matter, Earth and Atmospheric Physics, Astrophysics, Faculty of Physics, University of Bucharest, 405, Atomistilor Str., 077125 Magurele (Ilfov), Romania.

出版信息

Materials (Basel). 2023 Feb 16;16(4):1654. doi: 10.3390/ma16041654.

Abstract

In order to significantly reduce the computing time while, at the same time, keeping the accuracy and precision when determining the local values of the density and effective atomic number necessary for identifying various organic material, including explosives and narcotics, a specialized multi-stage procedure based on a multi-energy computed tomography investigation within the 20-160 keV domain was elaborated. It consisted of a compensation for beam hardening and other non-linear effects that affect the energy dependency of the linear attenuation coefficient (LAC) in the chosen energy domain, followed by a 3D fast reconstruction algorithm capable of reconstructing the local LAC values for 64 energy values from 19.8 to 158.4 keV, and, finally, the creation of a set of algorithms permitting the simultaneous determination of the density and effective atomic number of the investigated materials. This enabled determining both the density and effective atomic number of complex objects in approximately 24 s, with an accuracy and precision of less than 3%, which is a significantly better performance with respect to the reported literature values.

摘要

为了显著减少计算时间,同时在确定识别包括爆炸物和毒品在内的各种有机材料所需的密度和有效原子数的局部值时保持准确性和精度,精心设计了一种基于20 - 160 keV范围内多能计算机断层扫描研究的专门多阶段程序。它包括对束硬化和其他非线性效应的补偿,这些效应会影响所选能量域中线性衰减系数(LAC)的能量依赖性,随后是一种3D快速重建算法,该算法能够从19.8 keV到158.4 keV的64个能量值重建局部LAC值,最后创建一组算法,允许同时确定被研究材料的密度和有效原子数。这使得能够在大约24秒内确定复杂物体的密度和有效原子数,其准确度和精密度小于3%,相对于已报道的文献值而言,这是显著更好的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0728/9962467/beb8e32ad003/materials-16-01654-g0A1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验