Sparse Signal Reconstruction from Polychromatic X-ray CT Measurements via Mass Attenuation Discretization
Sparse Signal Reconstruction from Polychromatic X-ray CT Measurements via Mass Attenuation Discretization
复制标题
通过质量衰减离散化从多色 X 射线 CT 测量中重建稀疏信号
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Aleksandar Dogandzic
中科院分区：
文献类型：
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作者：
Renliang Gu;Aleksandar Dogandzic
提出了一种基于质量衰减系数离散化的多色x射线计算机断层扫描（ct）稀疏图像重建方法。假设被检物体的材料和入射光谱是未知的。我们重写的朗伯-比尔定律的质量衰减的积分表达式和离散所得的积分。然后，我们提出了一种惩罚约束最小二乘优化方法，用于从对数域测量中重建底层对象，其中采用活动集方法来估计入射能量密度参数，并使用负能量和平滑l1范数惩罚项来施加图像密度图的非负性和稀疏性。我们提出了一个两步的计划，通过使用更高的采样率的范围内具有较高的光子能量，并消除离散点，对前向投影模型的精度影响不大的质量衰减离散网格的细化。这个refi…
We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer’s law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth l1-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refi...