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Systematic implementation of spectral CT with a photon counting detector for liquid security inspection

机译:带光子计数检测器的光谱CT在液体安全检查中的系统实现

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X-ray liquid security inspection system plays an important role in homeland security, while the conventional dual-energy CT (DECT) system may have a big deviation in extracting the atomic number and the electron density of materials in various conditions. Photon counting detectors (PCDs) have the capability of discriminating the incident photons of different energy. The technique becomes more and more mature in nowadays. In this work, we explore the performance of a multi-energy CT imaging system with a PCD for liquid security inspection in material discrimination. We used a maximum-likelihood (ML) decomposition method with scatter correction based on a cross-energy response model (CERM) for PCDs so that to improve the accuracy of atomic number and electronic density imaging. Experimental study was carried to examine the effectiveness and robustness of the proposed system. Our results show that the concentration of different solutions in physical phantoms can be reconstructed accurately, which could improve the material identification compared to current available dual-energy liquid security inspection systems. The CERM-base decomposition and reconstruction method can be easily used to different applications such as medical diagnosis.
机译:X射线液体安全检查系统在国土安全中起着重要作用,而传统的双能CT(DECT)系统在各种条件下提取材料的原子序数和电子密度时可能会有很大的偏差。光子计数检测器(PCD)具有区分不同能量的入射光子的能力。如今,这项技术变得越来越成熟。在这项工作中,我们探索了带有PCD的多能量CT成像系统在材料鉴别中用于液体安全检查的性能。我们使用基于交叉能量响应模型(CERM)的PCD的最大似然(ML)散射校正方法,以提高原子序数和电子密度成像的准确性。进行了实验研究,以检验所提出系统的有效性和鲁棒性。我们的结果表明,可以精确地重建物理模型中不同溶液的浓度,与当前可用的双能液体安全检查系统相比,可以改善材料识别。基于CERM的分解和重建方法可以轻松地用于医疗诊断等不同应用。

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