Compressive spectral X-ray tomography based on spatial and spectral coded illumination
Compressive spectral X-ray tomography based on spatial and spectral coded illumination
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DOI：
10.1364/oe.27.010745
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发表时间：
2019-04-15
期刊：
影响因子：
3.8
通讯作者：
Arce, Gonzalo R.
中科院分区：
文献类型：
--
作者：
Cuadros, Angela;Ma, Xu;Arce, Gonzalo R.
光谱计算机断层扫描 (CT) 依靠 X 射线衰减系数的光谱依赖性将投影测量结果分成两个以上的能量仓。此类数据可用于揭示断层扫描材料特征——国家安全和医学成像的关键。本文探讨了与光谱成像中使用的传统方法的根本不同。它依靠 K 边缘编码孔径来创建空间和光谱编码的低剂量 X 射线束，以询问物体的特定体素。这种被称为压缩光谱 X 射线成像 (CSXI) 的新方法使用低成本标准 X 射线积分探测器并获取压缩测量结果，从而能够通过更少的测量结果重建能量分级图像。探索了用于结构照明的各种光谱和空间编码策略。 CSXI 中的子采样是通过视角光谱子采样、通过放置在源侧或探测器侧或两者的块-非块编码孔径启用的空间子采样来完成的。子采样策略、光谱滤波器、编码孔径及其位置的精心设计对于断层扫描图像重建的质量至关重要。 CSXI 的正向成像模型是一个非线性病态问题，我们对它进行了分析，并开发了一种多级算法来解决从积分探测器测量中估计能量分档正弦图的问题。然后，使用交替方向乘子法 (ADMM) 来解决联合稀疏和低秩优化问题，以利用能谱 X 射线数据立方体的结构进行重建。 (C) 2019 年美国光学学会根据 OSA 开放获取出版协议条款
Spectral computed tomography (CT) relies on the spectral dependence of X-ray attenuation coefficients to separate projection measurements into more than two energy bins. Such data can be used to unveil tomographic material characterization - key in national security and medical imaging. This paper explores a radical departure from conventional methods used in spectral imaging. It relies on K-edge coded apertures to create spatially and spectrally coded, lower-dose, X-ray bundles that interrogate specific voxels of the object. The new approach referred to as compressive spectral X-ray imaging (CSXI) uses low-cost standard X-ray integrating detectors and acquires compressive measurements, which enable the reconstruction of energy binned images from fewer measurements. Various spectral and spatial coding strategies for structured illumination are explored. Subsampling in CSXI is accomplished by either view angle spectral subsampling, spatial subsampling enabled by block-unblock coded apertures placed at the source or detector side, or both. The careful design of subsampling strategies, spectral filters, coded apertures, and their placement, are shown to be critical for the quality of tomographic image reconstruction. The forward imaging model of CSXI, which is a non-linear ill-posed problem, is analyzed and a multi-stage algorithm is developed to address the estimation of the energy binned sinograms from the integrating detector measurements. Then, an Alternating Direction Method of Multipliers (ADMM) is used to solve a joint sparse and low-rank optimization problem for reconstruction that exploits the structure of the spectral X-ray data cube. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement