Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging

doi:10.1088/1361-6560/ad360a

	Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging
	Zhang, Jianru1 ; Wang, Zhe2 ; Cao, Tuoyu 3; Cao, Guohua2 ; Ren, Wuwei1 ; Jiang, Jiahua 4
	2024-03-20
发表期刊	PHYSICS IN MEDICINE & BIOLOGY (IF:3.3[JCR-2023],3.4[5-Year])
ISSN	0031-9155
EISSN	1361-6560
卷号	69 期号:10
发表状态	已发表
DOI	10.1088/1361-6560/ad360a
摘要	Objective. We introduce a robust image reconstruction algorithm named residual-guided Golub-Kahan iterative reconstruction technique (RGIRT) designed for sparse-view computed tomography (CT), which aims at high-fidelity image reconstruction from a limited number of projection views. Approach. RGIRT utilizes an inner-outer dual iteration framework, with a flexible least square QR (FLSQR) algorithm implemented in the inner iteration and a restarted iterative scheme applied in the outer iteration. The inner FLSQR employs a flexible Golub-Kahan bidiagonalization method to reduce the size of the inverse problem, and a weighted generalized cross-validation method to adaptively estimate the regularization hyper-parameter. The inner iteration efficiently yields the intermediate reconstruction result, while the outer iteration minimizes the residual and refines the solution by using the result obtained from the inner iteration. Main results. The reconstruction performance of RGIRT is evaluated and compared to other reference methods (FBPConvNet, SART-TV, and FLSQR) using projection data from both numerical phantoms and real experimental Micro-CT data. The experimental findings, from testing various numbers of projection views and different noise levels, underscore the robustness of RGIRT. Meanwhile, theoretical analysis confirms the convergence of residual for our approach. Significance. We propose a robust iterative reconstruction algorithm for x-ray CT scans with sparse views, thereby shortening scanning time and mitigating excessive ionizing radiation exposure to small animals.
关键词	sparse-view CT image reconstruction inverse problem Golub-Kahan process regularization
URL	查看原文
收录类别	SCI ; EI
语种	英语
资助项目	National Natural Science Foundation of China["12101406","62105205","62273238"] ; null[21YF1429100]
WOS研究方向	Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:001209449700001
出版者	IOP Publishing Ltd
EI入藏号	20241916036862
EI主题词	Image reconstruction
EI分类号	723.5 Computer Applications ; 921.6 Numerical Methods
原始文献类型	Journal article (JA)
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/357360
专题	信息科学与技术学院_PI研究组_任无畏组信息科学与技术学院_硕士生生物医学工程学院生物医学工程学院_PI研究组_曹国华组
通讯作者	Cao, Guohua; Ren, Wuwei; Jiang, Jiahua
作者单位	1.School of Information Science and Technology, ShanghaiTech University 2.School of Biomedical Engineering, ShanghaiTech University 3.United Imaging Healthcare Co., Ltd 4.School of Mathematics, University of Birmingham, Edgbaston
第一作者单位	信息科学与技术学院
通讯作者单位	生物医学工程学院; 信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Zhang, Jianru,Wang, Zhe,Cao, Tuoyu,et al. Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging[J]. PHYSICS IN MEDICINE & BIOLOGY,2024,69(10).
APA	Zhang, Jianru,Wang, Zhe,Cao, Tuoyu,Cao, Guohua,Ren, Wuwei,&Jiang, Jiahua.(2024).Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging.PHYSICS IN MEDICINE & BIOLOGY,69(10).
MLA	Zhang, Jianru,et al."Robust residual-guided iterative reconstruction for sparse-view CT in small animal imaging".PHYSICS IN MEDICINE & BIOLOGY 69.10(2024).