IEEE Trans Med Imaging. 2018 Oct;37(10):2298-2309. doi: 10.1109/TMI.2018.2840841. Epub 2018 May 25.
By resolving the energy of the incident X-ray photons, spectral X-ray imaging with photon counting detectors offers additional material-specific information compared to conventional X-ray imaging. This additional information can be used to improve clinical diagnosis for various applications. However, spectral imaging still faces several challenges. Amplified noise and a reduced signal-to-noise ratio on the decomposed basis material images remain a major problem, especially for low-dose applications. Furthermore, it is challenging to construct an accurate model of the spectral measurement acquisition process. In this paper, we present a novel algorithm for projection-based material decomposition. It uses an empirical polynomial model that is tuned by calibration measurements. We combine this method with a statistical model of the measured photon counts and a dictionary-based joint regularization approach. We focused on spectral coronary angiography as a potential clinical application of projection-based material decomposition with photon counting detectors. Numerical and real experiments show that spectral angiography with realistic dose levels and gadolinium contrast agent concentrations are feasible using the proposed decomposition algorithm and currently available photon-counting detector technology.
与传统 X 射线成像相比，基于光子计数探测器的能谱 X 射线成像是通过解析入射 X 射线光子的能量，提供更多特定于物质的信息。这些额外的信息可用于改善各种应用的临床诊断。然而，光谱成像仍然面临着一些挑战。在分解的基础物质图像上，放大的噪声和降低的信噪比仍然是一个主要问题，特别是对于低剂量应用。此外，构建光谱测量采集过程的精确模型也具有挑战性。在本文中，我们提出了一种基于投影的材料分解的新算法。它使用通过校准测量来调整的经验多项式模型。我们将这种方法与测量光子计数的统计模型和基于字典的联合正则化方法相结合。我们专注于光谱冠状动脉造影术，将其作为基于投影的材料分解与光子计数探测器在潜在临床应用中的一个例子。数值和实际实验表明，使用所提出的分解算法和当前可用的光子计数探测器技术，在现实剂量水平和钆造影剂浓度下进行光谱血管造影是可行的。
