Improved Material Decomposition With a Two-Step Regularization for Spectral CT
Improved Material Decomposition With a Two-Step Regularization for Spectral CT
复制标题
通过光谱 CT 的两步正则化改进材料分解
DOI：
10.1109/access.2019.2950427
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发表时间：
2019-10
期刊：
影响因子：
3.9
通讯作者：
HENGYONG YU
中科院分区：
文献类型：
--
作者：
伍伟飞;吴伟文;陈佩君;VINCE VARUTRDHANABHUTI;HENGYONG YU
光谱计算机断层扫描（CT）的优点之一是它可以使用材料分解方法获得准确的材料成分。基于图像的材料分解是获取特定材料成分的常用方法，可分为图像重建和后材料分解两个步骤。为了获得精确的材料图，图像重建方法主要集中在通过结合正则化先验来改善图像质量。最近，正则化先验被引入到基于图像的迭代方法中的后材料分解过程中。由于正则化先验可以结合到图像重建和后图像域材料分解中，因此结合这两种情况的正则化性能仍然是一个悬而未决的问题。为了实现这一目标，首先分析和比较这些步骤的材料精度。然后，为了进一步提高分解材料的准确性，开发了一种基于两步正则化的方法，通过将先验知识引入图像重建和后材料分解。数值模拟和临床前小鼠实验都证明了基于两步正则化的方法在提高材料精度方面的优势。
One of the advantages of spectral computed tomography (CT) is it can achieve accurate material components using the material decomposition methods. The image-based material decomposition is a common method to obtain specific material components, and it can be divided into two steps: image reconstruction and post material decomposition. To obtain accurate material maps, the image reconstruction method mainly focuses on improving image quality by incorporating regularization priors. Very recently, the regularization priors are introduced into the post material decomposition procedure in the iterative image-based methods. Since the regularization priors can be incorporated into image reconstruction and post image-domain material decomposition, the performance of regularization by combining these two cases is still an open problem. To realize this goal, the material accuracy from those steps are first analyzed and compared. Then, to further improve the accuracy of decomposition materials, a two-step regularization based method is developed by incorporating priors into image reconstruction and post material decomposition. Both numerical simulation and preclinical mouse experiments are performed to demonstrate the advantages of the two-step regularization based method in improving material accuracy.
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