[1] Herman G T. Fundamentals of computerized tomography: image reconstruction from projections[M]. Berlin: Springer Science & Business Media(2009).

[2] Kachelrieß M, Watzke Oliver, Kalender W A. Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT[J]. Medical Physics, 28, 475-490(2001). http://scitation.aip.org/content/aapm/journal/medphys/28/4/10.1118/1.1358303

[3] Ma C X, Hu J J, Yan B. Optimization of fan-beam CT filtered backprojection reconstruction algorithm[J]. Laser & Optoelectronics Progress, 49, 091103(2012).

[4] Zhang H, Han H, Wang J et al. Deriving adaptive MRF coefficients from previous normal-dose CT scan for low-dose image reconstruction via penalized weighted least-squares minimization[J]. Medical Physics, 41, 041916(2014). http://scitation.aip.org/content/aapm/journal/medphys/41/4/10.1118/1.4869160

[5] Zhang H, Han H. LiangJ, et al. Extracting information from previous full-dose CT scan for knowledge-based Bayesian reconstruction of current low-dose CT images[J]. IEEE Transactions on Medical Imaging, 35, 860-870(2015). http://europepmc.org/abstract/MED/26561284

[6] Lian Q S, Hao P P. Image reconstruction for CT based on compressed sensing and ART[J]. Optical Technique, 35, 422-425(2009).

[7] Lauzier P T, Chen G H. Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction[J]. Medical Physics, 40, 021902(2013). http://www.ncbi.nlm.nih.gov/pubmed/23387750

[8] Zhang Y L, Kong H H, Pan J X et al. Spectral computed tomographic image reconstruction based on split-bregman algorithm[J]. Acta Optica Sinica, 37, 0411003(2017).

[9] Ertas M, Akan A, Yildirim I et al. An iterative reconstruction for tomosynthesis imaging using non-local means. [C]∥Proceedings of IEEE International Conference on Imaging Systems and Techniques, 325-328(2014).

[10] Chen J L, Wang L Y, Yan B et al. Efficient and robust 3D CT image reconstruction based on total generalized variation regularization using the alternating direction method[J]. Journal of X-Ray Science and Technology, 23, 683-699(2015). http://www.ncbi.nlm.nih.gov/pubmed/26756406

[11] Bredies K, Kunisch K, Pock T. Total generalized variation[J]. SIAM Journal on Imaging Sciences, 3, 492-526(2010).

[12] Dabov K, Foi A, Egiazarian K. Image denoising with block-matching and 3D filtering[J]. Proceedings of SPIE, 6064, 354-365(2006). http://spie.org/Publications/Proceedings/Paper/10.1117/12.643267

[13] Wang L Y, Zhang H M, Cai A L et al. Image reconstruction algorithm based on inexact alternating direction total-variation minimization[J]. Acta Physica Sinica, 62, 198701(2013).

[14] Sidky E Y, Kao C M, Pan X. Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT[J]. Journal of X-ray Science and Technology, 14, 119-139(2009). http://cn.arxiv.org/abs/0904.4495

[15] Li T F, Li X, Wang J et al. Nonlinear sinogram smoothing for low-dose X-ray CT[J]. IEEE Transactions on Nuclear Science, 51, 2505-2513(2004). http://jicru.oxfordjournals.org/external-ref?access_num=10.1109/TNS.2004.834824&link_type=DOI

[16] Wen Z W, Yin W T, Goldfarb D et al. A fast algorithm for sparse reconstruction based on shrinkage, subspace optimization, and continuation[J]. SIAM Journal on Scientific Computing, 32, 1832-1857(2010). http://dl.acm.org/citation.cfm?id=1958654.1958661

[17] Xiao Y H, Song H N. Aninexact alternating directions algorithm for constrained total variation regularized compressive sensing problems[J]. Journal of Mathematical Imaging and Vision, 44, 114-127(2012). http://link.springer.com/article/10.1007/s10851-011-0314-y

[18] Li C B, Yin W T, Jiang H et al. An efficient augmented Lagrangian method with applications to total variation minimization[J]. Computational Optimization and Applications, 56, 507-530(2013). http://www.ams.org/mathscinet-getitem?mr=3128747