[1] La Rivière P J, Billmire D M. Reduction of noise-induced streak artifacts in X-ray computed tomography through spline-based penalized-likelihood sinogram smoothing[J]. IEEE Transactions on Medical Imaging, 24, 105-111(2005).

[2] La Rivière P J, Bian J G, Vargas P A. Penalized-likelihood sinogram restoration for computed tomography[J]. IEEE Transactions on Medical Imaging, 25, 1022-1036(2006).

[3] Lu H B, Hsiao I T, Li X et al. Noise properties of low-dose CT projections and noise treatment by scale transformations[J]. IEEE Nuclear and Plasma Sciences Society, 4, 1662-1666(2001).

[4] Lu H B, Li X, Li L H et al. Adaptive noise reduction toward low-dose computed tomography[J]. Proceedings of SPIE, 5030, 759-766(2003).

[5] Foi A, Trimeche M, Katkovnik V et al. Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data[J]. IEEE Transactions on Image Processing, 17, 1737-1754(2008).

[6] Ye S Q, Ravishankar S, Long Y et al. SPULTRA: low-dose CT image reconstruction with joint statistical and learned image models[J]. IEEE Transactions on Medical Imaging, 39, 729-741(2020).

[7] Fu L, Lee T C, Kim S M et al. Comparison between pre-log and post-log statistical models in ultra-low-dose CT reconstruction[J]. IEEE Transactions on Medical Imaging, 36, 707-720(2017).

[8] Whiting B R. Signal statistics of X-ray computed tomography[J]. Proceedings of SPIE, 4682, 53-60(2002).

[9] Whiting B R, Massoumzadeh P, Earl O A et al. Properties of preprocessed sinogram data in X-ray computed tomography[J]. Medical Physics, 33, 3290-3303(2006).

[10] Gonzalo V S F, Raúl S J E. Statistical characterization of the linear attenuation coefficient in polychromatic CT scans[J]. Medical Physics, 47, 5568-5581(2020).

[11] Ji D J, Qu G R, Hu C H et al. Contrast enhancement method based on synchrotron radiation CT image reconstruction[J]. Laser & Optoelectronics Progress, 57, 221024(2020).

[12] Li L, Jin H, Liu J et al. Adaptive 3D mesh model reconstruction based on industrial CT images[J]. Acta Optica Sinica, 43, 0334001(2023).

[13] Liu H X, Zhao Y M, Zhang C L et al. Study on tooth cone beam CT image reconstruction based on improved U-net network[J]. Chinese Journal of Lasers, 49, 2407207(2022).

[14] Wei Y L, Yang Z Y, Xia W J et al. Low dose CT denoising based on subspace projection and edge enhancement[J]. Computerized Tomography Theory and Applications, 31, 721-729(2022).

[15] Di Y X, Kong H H, Niu X W. Research on multi-energy spectrum CT image analysis method based on principal component analysis[J]. Computerized Tomography Theory and Applications, 31, 749-760(2022).

[16] Seri R, Choirat C. Comparison of approximations for compound Poisson processes[J]. ASTIN Bulletin, 45, 601-637(2015).

[17] Mao S S[M]. Advanced probability and statistics(2002).

[18] Sun H Y, Hu H C. P-norm distribution and its sampling distributions[J]. Chinese Journal of Applied Probability and Statisties, 19, 424-428(2003).

[19] Huber P J. Robust regression: asymptotics, conjectures and Monte Carlo[J]. The Annals of Statistics, 1, 799-821(1973).

[20] Sun H Y. Approximate representation of the p-norm distribution[J]. Geomatics and Information Science of Wuhan University, 26, 222-225(2001).

[21] Wei B C[M]. A course in parametric statistics(2006).

[22] CryerJ D, ChanK S, 潘红宇[M]. 时间序列分析及应用(2011).

     Cryer J D, Chan K S, Pan H Y[M]. Time series analysis with applications(2011).

[23] Ducros N, Abascal J, Sixou B et al. Regularization of nonlinear decomposition of spectral X-ray projection images[J]. Medical Physics, 44, e174-e187(2017).