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首页> 外文期刊>Journal of Medical Imaging and Health Informatics >Numerical and Monte Carlo Simulation on X-ray Fluorescence Computed Tomography with Self-Absorption Correction
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Numerical and Monte Carlo Simulation on X-ray Fluorescence Computed Tomography with Self-Absorption Correction

机译：具有自吸收校正功能的X射线荧光计算机断层扫描的数值和蒙特卡罗模拟

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摘要

As a promising imaging technique, X-ray fluorescence computed tomography (XFCT) can provide us the distribution of trace elements within samples in a nondestructive and noninvasive manner. However, self-absorption has seriously affected the quality of reconstruction image. In this investigation, the feasibility of projection matrix based on Siddon algorithm used for self-absorption correction in pencil-beam XFCT was test by numerical and Monte Carlo simulation. The PMMA (polymethyl methacrylate) phantom (diameter = 3.2 cm) contained one GNP (gold nanoparticles)-loaded region (diameter = 0.6 cm) is imaged using numerical and Monte Carlo simulation. Three algorithms, including Filter Back Projection (FBP), Algebra Reconstruction Technique (ART) and maximum likelihood expectation maximization (MLEM), were used to reconstruct images, then, Au weight concentration, relative error and contrast-to-noise (CNR) were calculated.
机译：作为一种很有前途的成像技术，X射线荧光计算机断层扫描（XFCT）可以无损且无创的方式为我们提供样品中痕量元素的分布。但是，自吸收严重影响了重建图像的质量。在这项研究中，通过数值和蒙特卡洛模拟测试了基于Siddon算法的投影矩阵用于笔形XFCT自吸收校正的可行性。使用数值和蒙特卡罗模拟对包含一个GNP（金纳米粒子）负载区域（直径= 0.6 cm）的PMMA（聚甲基丙烯酸甲酯）模型（直径= 3.2 cm）进行成像。包括滤波反投影（FBP），代数重构技术（ART）和最大似然期望最大化（MLEM）在内的三种算法被用于重构图像，然后，Au权重集中，相对误差和对比噪声（CNR）分别为计算。

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