论文标题

用于CT材料分解的空间光谱过滤器的物理建模和性能

Physical Modeling and Performance of Spatial-Spectral Filters for CT Material Decomposition

论文作者

Tivnan, Matthew, Tilley II, Steven, Stayman, J. Webster

论文摘要

通过光谱CT:一种将多个光子能谱敏感性纳入单个数据收集的模态,用于成像单个采集中多种对比剂的材料分解已成为可能。这项工作介绍了对光谱CT的新方法的研究,该方法不依赖于散歧视探测器或多个X射线源。取而代之的是,将K边滤波器的瓷砖图案放在X射线的前面,以创建空间编码的光谱数据。为了改善采样,相对于来源,空间光谱过滤器是连续移动的。采用基于模型的材料分解算法来直接从每个光谱通道中稀疏的投影数据中直接重建多个材料密度。与移动过滤器的X射线焦点斑点大小和运动模糊相关的物理效果预计将影响整体性能。在这项工作中,对这些物理效果进行了建模,并进行了性能分析。具体而言,实验以0.2 mm至4.0 mm之间的模拟焦点宽度表示。此外,对于50 mm/s和450 mm/s的线性翻译速度,对滤波器运动模糊进行了模拟。 0.2 mM和1.0 mm焦点之间的性能差异小于15%,表明使用逼真的X射线管的方法可行性。此外,对于合理的滤波器驱动速度,尽管基于运动的光谱模糊,但显示出更高的速度可减少误差(由于采样的改进)。

Material decomposition for imaging multiple contrast agents in a single acquisition has been made possible by spectral CT: a modality which incorporates multiple photon energy spectral sensitivities into a single data collection. This work presents an investigation of a new approach to spectral CT which does not rely on energy-discriminating detectors or multiple x-ray sources. Instead, a tiled pattern of K-edge filters are placed in front of the x-ray to create spatially encoded spectra data. For improved sampling, the spatial-spectral filter is moved continuously with respect to the source. A model-based material decomposition algorithm is adopted to directly reconstruct multiple material densities from projection data that is sparse in each spectral channel. Physical effects associated with the x-ray focal spot size and motion blur for the moving filter are expected to impact overall performance. In this work, those physical effects are modeled and a performance analysis is conducted. Specifically, experiments are presented with simulated focal spot widths between 0.2 mm and 4.0 mm. Additionally, filter motion blur is simulated for a linear translation speeds between 50 mm/s and 450 mm/s. The performance differential between a 0.2 mm and a 1.0 mm focal spot is less than 15% suggesting feasibility of the approach with realistic x-ray tubes. Moreover, for reasonable filter actuation speeds, higher speeds are shown to decrease error (due to improved sampling) despite motion-based spectral blur.

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