摘要
基于光子计数探测器的能谱CT在材料分解、组织表征、病变检测等应用中具有巨大的潜力。在重建过程中,通道数的增加会造成单通道中光子数减少,从而导致重建图像质量下降,难以满足实际需求。本文从能谱CT重建的角度出发,将广义总变分向矢量延伸,利用奇异值的稀疏性,促进图像梯度的线性依赖,提出一种基于核范数的多通道联合广义总变分的能谱CT重建算法。在图像重建过程中,多层共享结构信息,同时保留独特的差异。实验结果表明,本文提出的算法在抑制噪声的同时,能够更有效地恢复图像细节及边缘信息。
Spectral computed tomography(CT)based on photon-counting detectors,has great potential in material decomposition,tissue characterization,lesion detection,and other applications.During the reconstruction,the in-crease of the number of channels will reduce the photon number in a single channel,resulting in the decline of the quality of the reconstructed image,which is difficult to meet the actual needs.To improve the quality of image re-construction,joint multi-channel total generalized variational based on the unclear norm for spectral CT reconstruc-tion was proposed in this paper.The algorithm will extend total generalized variation to the vector,and the sparsity of singular values is used to promote the linear dependence of the image gradient.The structural information of the multi-channel image is shared during the image reconstruction process while unique differences are preserved.Experimental results show that the proposed algorithm can effectively recover image details and marginal informa-tion while suppressing noise.
作者
连祥媛
孔慧华
潘晋孝
高文波
王攀
Lian Xiangyuan;Kong Huihua;Pan Jinxiao;Gao Wenbo;Wang Pan(School of Science,North University of China,Taiyuan,Shanxi 030051,China;Shanxi Key Laboratory of Signal Capturing&Processing,North University of China,Taiyuan,Shanxi 030051,China;Hunan Vsngusrd Group.Co.Ltd,Chenxi,Hunan 419503,China)
出处
《光电工程》
CAS
CSCD
北大核心
2021年第9期66-74,共9页
Opto-Electronic Engineering
基金
国家自然科学基金资助项目(61801437,61871351,61971381)。
关键词
CT重建
能谱CT
广义总变分
核范数
多通道联合
CT reconstruction
spectral CT
total generalized variation
nuclear norm
joint multi-channel
