• Laser & Optoelectronics Progress
  • Vol. 58, Issue 12, 1210031 (2021)
Yu Li1、2、*, Na Shi1, Huihua Kong1、2、**, and Xiaoxue Lei1、2
Author Affiliations
  • 1College of Science, North University of China, Taiyuan, Shanxi 0 30051, China
  • 2Shanxi Key Laboratory of Signal Capturing & Processing, North University of China, Taiyuan, Shanxi 0 30051, China;
  • show less
    DOI: 10.3788/LOP202158.1210031 Cite this Article Set citation alerts
    Yu Li, Na Shi, Huihua Kong, Xiaoxue Lei. Sparse Angle CT Reconstruction Algorithm Based on Total Variation and Convolutional Sparse Coding in Gradient Domain[J]. Laser & Optoelectronics Progress, 2021, 58(12): 1210031 Copy Citation Text show less
    References

    [1] Brenner D J, Hall E J. Computed tomography: an increasing source of radiation exposure[J]. The New England Journal of Medicine, 357, 2277-2284(2007). http://www.bmj.com/lookup/external-ref?access_num=10.1056/NEJMra072149&link_type=DOI

    [2] Smith P R, Peters T M, Bates R T et al. Image reconstruction from finite numbers of projections[J]. Journal of Physics A: Mathematical, Nuclear and General, 6, 361-382(1973). http://adsabs.harvard.edu/cgi-bin/nph-data_query?link_type=ABSTRACT&bibcode=1973JPhA....6..361S

    [3] Li Y S, Chen Y, Hu Y N et al. Strategy of computed tomography sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation[J]. Journal of the Optical Society of America A, Optics, Image Science, and Vision, 29, 153-163(2012).

    [4] Bian J, Siewerdsen J H, Han X et al. Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT[J]. Physics in Medicine and Biology, 55, 6575-6599(2010). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3597413/

    [5] Wang M S, Zhang Y B, Liu R et al. An adaptive reconstruction algorithm for spectral CT regularized by a reference image[J]. Physics in Medicine and Biology, 61, 8699-8719(2016).

    [6] Yu Z C, Leng S, Li Z B et al. Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography[J]. Physics in Medicine and Biology, 61, 6707-6732(2016). http://pubmedcentralcanada.ca/pmcc/articles/PMC5056833/

    [7] Sidky E Y, Pan X. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization[J]. Physics in Medicine and Biology, 53, 4777-4807(2008). http://pubmedcentralcanada.ca/pmcc/articles/PMC2630711/

    [8] Tang S J, Tang X Y. Statistical CT noise reduction with multi-scale decomposition and penalized weighted least square for incomplete projection data[J]. Proceedings of SPIE, 8668, 866839(2013). http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1661984

    [9] Elbakri I A, Fessler J A. Statistical image reconstruction for polyenergetic X-ray computed tomography[J]. IEEE Transactions on Medical Imaging, 21, 89-99(2002).

    [10] Xu Q, Yu H Y, Mou X Q et al. Low-dose X-ray CT reconstruction via dictionary learning[J]. IEEE Transactions on Medical Imaging, 31, 1682-1697(2012). http://www.ncbi.nlm.nih.gov/pubmed/22542666

    [11] Chen Y, Shi L Y, Feng Q J et al. Artifact suppressed dictionary learning for low-dose CT image processing[J]. IEEE Transactions on Medical Imaging, 33, 2271-2292(2014). http://ieeexplore.ieee.org/document/6851914

    [12] Chen P J, Feng P, Wu W W et al. Material discrimination by multi-spectral CT based on image total variation and tensor dictionary[J]. Acta Optica Sinica, 38, 1111002(2018).

    [13] Liu J, Kang Y Q, Gu Y B et al. Low dose computed tomography image reconstruction based on sparse tensor constraint[J]. Acta Optica Sinica, 39, 0811004(2019).

    [14] Chen X Y, Zhang W J, Sun W Z et al. Super-resolution reconstruction of images based on multi-scale and multi-residual network[J]. Laser & Optoelectronics Progress, 57, 181009(2020).

    [15] Zeiler M D, Krishnan D, Taylor G W et al. Deconvolutional networks[C]. //2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA., 2528-2535(2010).

    [16] Xiong J J, Lu H Y, Zhan M H et al. Convolutional sparse coding in gradient domain for MRI reconstruction[J]. Acta Automatica Sinica, 43, 1841-1849(2017).

    [17] Bao P, Xia W J, Yang K et al. Convolutional sparse coding for compressed sensing CT reconstruction[J]. IEEE Transactions on Medical Imaging, 38, 2607-2619(2019). http://www.ncbi.nlm.nih.gov/pubmed/30908204

    [18] Fu L L, Ren C, He X H et al. Super-resolution reconstruction based on sparse coding and anisotropic filtering[J]. Information Technology and Network Security, 39, 23-28(2020).

    [19] Wohlberg B. Convolutional sparse representations with gradient penalties[C]. //2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 15-20, 2018, Calgary, AB, Canada., 6528-6532(2018).

    [20] Boyd S, Parikh N, Chu E et al. Distributed optimization and statistical learning via the alternating direction method of multipliers[J]. Foundations and Trends© in Machine Learning, 3, 1-122(2010). http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=8186925

    [21] Dias J M B, Figueiredo M A T. A new TwIST: two-step iterative shrinkage/thresholding algorithms for image restoration[J]. IEEE Transactions on Image Processing, 16, 2992-3004(2007).

    [22] Siddon R L. Fast calculation of the exact radiological path for a three-dimensional CT array[J]. Medical Physics, 12, 252-255(1985). http://onlinelibrary.wiley.com/doi/10.1118/1.595715/abstract

    [24] Sidky E Y, Kao C M, Pan X C et al. Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT[EB/OL]. (2009-04-28)[2020-04-20]. https://arxiv.org/abs/0904.4495

    [25] Shen Z Q, Gong C C, Yu W et al. Guided image filtering reconstruction based on total variation and prior image for limited-angle CT[J]. IEEE Access, 8, 151878-151887(2020).

    Yu Li, Na Shi, Huihua Kong, Xiaoxue Lei. Sparse Angle CT Reconstruction Algorithm Based on Total Variation and Convolutional Sparse Coding in Gradient Domain[J]. Laser & Optoelectronics Progress, 2021, 58(12): 1210031
    Download Citation