论文标题
一种用于基于模型的迭代CT重建和材料分解的预处理算法
A Preconditioned Algorithm for Model-Based Iterative CT Reconstruction and Material Decomposition from Spectral CT Data
论文作者
论文摘要
基于模型的材料分解是一个统计介绍重建框架，其中直接从光谱CT数据估算了基材料密度。这种方法是用于多能X射线传输和阳台的物理模型，因此通常不会遭受束缚的伪像。但是，由于基本材料之间的强烈反行关系，该估计是一个不当的反问题。在这项工作中，我们提出了一种针对非线性惩罚加权平方英尺目标函数的优先优化算法。
Model-based material decomposition is a statisticaliterative reconstruction framework where basis material densityimages are estimated directly from spectral CT data. This methoduses a physical model for polyenergetic x-ray transmission andattenuation and therefore it does not typically suffer frombeam-hardening artifacts. However, this estimation is a poorly-conditioned inverse problem due to the strong anticorrelationbetween basis materials. In this work we propose an precondi-tioned optimization algorithm for a nonlinear penalized weightedleast-squares objective function.
