Sparse X-ray CT image reconstruction and blind beam hardening correction via mass attenuation discretization
Sparse X-ray CT image reconstruction and blind beam hardening correction via mass attenuation discretization
复制标题
通过质量衰减离散化进行稀疏 X 射线 CT 图像重建和盲束硬化校正
DOI：
--
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Aleksandar Dogandzic
中科院分区：
文献类型：
--
作者：
Renliang Gu;Aleksandar Dogandzic
我们发展了一种非线性稀疏X射线计算机层析成像(CT)图像重建方法，该方法考虑了多色X射线源的射束硬化效应。我们采用被检测物体的材料和入射多色源光谱未知的盲目场景，并对模拟无噪声测量的基本积分表达式进行质量衰减离散化。我们的重建算法使用惩罚最小二乘代价函数的约束最小化，其中对入射光谱参数施加非负性和最大能量约束，并引入负能量和光滑的L1范数惩罚项来确保密度图图像的非负性和稀疏性。这种最小化方案在用于估计密度图图像的非线性共轭梯度步长和用于估计入射谱参数的活动集步长之间交替。我们将该方法与现有的方法进行了比较，这些方法忽略了测量值的多色性或密度图图像的稀疏性。
We develop a nonlinear sparse X-ray computed tomography (CT) image reconstruction method that accounts for beam hardening effects due to polychromatic X-ray sources. We adopt the blind scenario where the material of the inspected object and the incident polychromatic source spectrum are unknown and apply mass attenuation discretization of the underlying integral expressions that model the noiseless measurements. Our reconstruction algorithm employs constrained minimization of a penalized least-squares cost function, where nonnegativity and maximum-energy constraints are imposed on incident spectrum parameters and negative-energy and smooth l1-norm penalty terms are introduced to ensure the nonnegativity and sparsity of the density map image. This minimization scheme alternates between a nonlinear conjugate-gradient step for estimating the density map image and an active set step for estimating incident spectrum parameters. We compare the proposed method with the existing approaches, which ignore the polychromatic nature of the measurements or sparsity of the density map image.
通过 ECME 硬阈值重建稀疏信号
影响因子：
5.4
作者：
Qiu, Kun;Dogandzic, Aleksandar
通讯作者：
Dogandzic, Aleksandar