基于Split-Bregman算法的能谱计算机层析图像重建

发布时间：2018-03-15 02:37

本文选题：成像系统　切入点：能谱计算机层析图像重建　出处：《光学学报》2017年04期 　论文类型：期刊论文

【摘要】：与传统计算机层析(CT)成像技术相比,能谱CT可在一次扫描中得到物体在不同能谱通道下的投影图像,这有利于区分物体的材质,提高信号噪声比。基于光子计数探测器的能谱CT是近年来成像领域研究的热点。由于能谱通道变窄,每个能谱通道内的噪声增加。为了有效降低通道内的噪声,采用基于全变分最小化的SplitBregman算法进行图像重建。根据重建模体的先验信息,进行能谱通道的划分;采用Split-Bregman算法对含噪声和稀疏角的能谱投影数据进行重建。仿真结果表明,基于Split-Bregman算法的能谱CT图像重建方法能够有效减少能谱通道内噪声的影响,满足物体材质区分的需求。
[Abstract]:Compared with traditional computer tomography (CT) imaging techniques, EDS CT can obtain projection images of objects in different energy spectrum channels in a single scan, which is helpful to distinguish the materials of objects. In recent years, spectral CT based on photon counting detector is a hot spot in imaging field. Because the energy spectrum channel becomes narrower, the noise in each energy spectrum channel increases. In order to reduce the noise in the channel effectively, The SplitBregman algorithm based on total variational minimization is used to reconstruct the image. According to the priori information of the remodeled volume, the energy spectrum channels are partitioned. The spectral projection data with noise and sparse angle are reconstructed by Split-Bregman algorithm. The simulation results show that, Spectral CT image reconstruction method based on Split-Bregman algorithm can effectively reduce the influence of noise in the energy spectrum channel and meet the needs of material differentiation.
【作者单位】：中北大学理学院;中北大学信息探测与处理山西省重点实验室;中北大学电子测试技术国家重点实验室;
【基金】：国家自然科学基金(61601412,61571404,61471325) 山西省自然科学基金(2015021099) 山西省高等学校优秀青年学术带头人支持计划
【分类号】：TP391.41

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