Comparison of few-view CT image reconstruction algorithms by constrained total-variation minimization based on different sampling bases

被引:0
|
作者
Wang, Haoyu [1 ]
Xie, Yaoqin [1 ]
Bao, Shanglian [1 ]
Li, Lei [2 ]
Yan, Bin [2 ]
机构
[1] Peking Univ, Beijing City Key Lab Med Phys & Engn, 201 Chengfu Rd, Beijing 100871, Peoples R China
[2] Informat Engn Univ, Inst Informat Engn, Dept Informat Res, Zhengzhou, Peoples R China
基金
美国国家科学基金会;
关键词
convex optimization; total-variation minimization; sparsity; incoherence; orthogonal basis; UNCERTAINTY PRINCIPLES; SIGNAL RECOVERY;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The aim of this paper is to investigate how the choice of the sampling basis affects the reconstruction results of constrained total-variation (TV) minimization algorithms used for few-view computed tomography (CT). The reconstruction results between the algorithm based on frequency samples (AFS) and the algorithm based on projection samples (APS) are compared using numerical simulated data. Under same conditions, AFS exhibits better results compared with APS. These experimental results confirm that provided same conditions, the more incoherence between the basis for sampling Psi and the basis of the sparse signal Phi, the better reconstruction results of the constrained TV minimization algorithm can be achieved and better algorithms can be developed with the basis pairs (Phi, Psi).
引用
收藏
页码:443 / 446
页数:4
相关论文
共 50 条
  • [1] Improved total variation minimization method for few-view computed tomography image reconstruction
    Zhanli Hu
    Hairong Zheng
    BioMedical Engineering OnLine, 13
  • [2] Improved total variation minimization method for few-view computed tomography image reconstruction
    Hu, Zhanli
    Zheng, Hairong
    BIOMEDICAL ENGINEERING ONLINE, 2014, 13
  • [3] Few-view CT image reconstruction using improved total variation regularization
    Li, Kuai
    Sang, Ziru
    Zhang, Xuezhu
    Zhang, Mengxi
    Jiang, Changhui
    Zhang, Qiyang
    Ge, Yongshuai
    Liang, Dong
    Yang, Yongfeng
    Liu, Xin
    Zheng, Hairong
    Hu, Zhanli
    JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY, 2019, 27 (04) : 739 - 753
  • [4] High resolution image reconstruction with constrained, total-variation minimization
    Sidky, Emil Y.
    Chartrand, Rick
    Duchin, Yuval
    Ullberg, Christer
    Pan, Xiaochuan
    2010 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD (NSS/MIC), 2010, : 2617 - 2620
  • [6] Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction
    Zhang, Hanming
    Wang, Linyuan
    Yan, Bin
    Li, Lei
    Cai, Ailong
    Hu, Guoen
    PLOS ONE, 2016, 11 (02):
  • [7] Few-view image reconstruction with fractional-order total variation
    Zhang, Yi
    Zhang, Weihua
    Lei, Yinjie
    Zhou, Jiliu
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2014, 31 (05) : 981 - 995
  • [8] Prior Image based Anisotropic Edge Guided TV Minimization for Few-View CT Reconstruction
    Rong, Junyan
    Gao, Peng
    Liu, Wenlei
    Liao, Qimei
    Jiao, Chun
    Lu, Hongbing
    2014 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE (NSS/MIC), 2014,
  • [9] Constrained - Total - Variation - Minimization - Based Image Reconstruction in Breast CT
    Bian, J.
    Yang, K.
    Han, X.
    Sidky, E.
    Boone, J.
    Pan, X.
    MEDICAL PHYSICS, 2011, 38 (06)
  • [10] Fast minimization methods for solving constrained total-variation superresolution image reconstruction
    Michael Ng
    Fan Wang
    Xiao-Ming Yuan
    Multidimensional Systems and Signal Processing, 2011, 22 : 259 - 286