Model-based Multi-material Decomposition using Spatial-Spectral CT Filters.

J Webster Stayman, Steven Tilley
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Abstract

Spectral CT with multiple contrast agents has been enabled by energy-discriminating detectors with multiple spectral channels. We propose a new approach that uses spatial-spectral filters to provide multiple beamlets with different incident spectra for spectral channels based on "source-side" control. Since these spatial-spectral filters yield spectral channels that are sparse, we adopt model-based material decomposition to directly reconstruct material densities from projection data. Simulation studies in three-and four-material decomposition experiments show the underlying feasibility of the spatial-spectral filtering technique. This methodology has the potential to facilitate imaging of multiple contrast agents simultaneously with relatively simple hardware, or to improve spectral CT performance via combination with other established spectral CT methods for additional control and flexibility.

Abstract Image

Abstract Image

Abstract Image

利用空间光谱 CT 滤波器进行基于模型的多材料分解。
具有多个光谱通道的能量鉴别探测器可实现使用多种造影剂的光谱 CT。我们提出了一种新方法,利用空间光谱滤波器为基于 "源侧 "控制的光谱通道提供具有不同入射光谱的多个小波束。由于这些空间光谱滤波器产生的光谱通道是稀疏的,因此我们采用基于模型的材料分解,直接从投影数据重建材料密度。在三材料分解和四材料分解实验中进行的模拟研究表明,空间光谱滤波技术是可行的。这种方法有可能促进使用相对简单的硬件同时对多种造影剂进行成像,或通过与其他已有的光谱 CT 方法相结合来提高光谱 CT 的性能,从而实现额外的控制和灵活性。
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