[1] Seferis I, Michail C, Valais I, et al.. Imaging performance of a thin Lu2O3∶Eu nanophosphor scintillating screen coupled to a high resolution CMOS sensor under X-ray radiographic conditions: Comparison with Gd2O2S∶Eu conventional phosphor screen[C]. SPIE, 2014, 9033: 90333T.
[2] Sun C, Pratx G, Carpenter C M, et al.. Synthesis and radioluminescence of PEGylated Eu3+-doped nanophosphors as bioimaging probes [J]. Advanced Materials, 2011, 23(24): H195-H199.
[3] Pratx G, Carpenter C M, Sun C, et al.. X-ray luminescence computed tomography via selective excitation: A feasibility study[J]. IEEE Transactions on Medical Imaging, 2010, 29(12): 1992-1999.
[4] Jin Chen, Guo Hongbo, Hou Yuqing, et al.. Biolunminescence tomography reconstruction based on simplified spherical harmonics approximation model and sparse reconstruction by separable approximation[J]. Acta Optica Sinica, 2014, 34(6): 0617001.
[5] Liu Hejuan, Hou Yuqing, He Xiaowei, et al.. A comparative study and evaluation on several typical iterative methods for bioluminescence tomography[J]. Laser & Optoelectronics Progress, 2015, 52(8): 081704.
[6] Yu J, Cheng J, Hou Y, et al.. Sparse reconstruction for fluorescence molecular tomography via a fast iterative algorithm[J]. Journal of Innovative Optical Health Sciences, 2014, 7(3): 145008.
[7] Guo Hongbo, He Xiaowei, Hou Yuqing, et al.. Fluorescence molecular tomography based on nonconvex sparse regularization[J]. Acta Optica Sinica, 2015, 35(7): 0717001.
[8] Dong Fang, Hou Yuqing, Yu Jingjing, et al.. Fluorescence molecular tomography via greedy method combined with region-shrinking strategy[J]. Laser & Optoelectronics Progress, 2015, 32(10): 245519.
[9] Pratx G, Carpenter C M, Sun C, et al.. Tomographic molecular imaging of X-ray-excitable nanoparticles[J]. Optics Letters, 2010, 35(20): 3345-3347.
[10] Cong W, Shen H, Wang G. Spectrally resolving and scattering-compensated X-ray luminescence/fluorescence computed tomography [J]. Journal of Biomedical Optics, 2011, 16(6): 409-416.
[11] Chen D,Zhu S, Yi H, et al.. Cone beam X-ray luminescence computed tomography: A feasibility study[J]. Medical Physics, 2013, 40(3): 031111.
[12] Liu X, Liao Q, Wang H. In vivo X-ray luminescence tomographic imaging with single-view data[J]. Optics Letters, 2013, 38(22): 4530- 4533.
[13] Klose A D, Ntziachristos V, Hielscher A H. The inverse source problem based on the radiative transfer equation in optical molecular imaging [J]. Journal of Computational Physics, 2005, 202(1): 323-345.
[14] Afonso M V, Bioucas-Dias J M, Ma F. Fast image recovery using variable splitting and constrained optimization[J]. IEEE Transactions on Image Processing, 2010, 19(9): 2345-2356.
[15] Figueiredo M A T, Bioucas-Dias J M, Afonso M V. Fast frame-based image deconvolution using variable splitting and constrained optimization[C]. IEEE Workshop on Statistical Signal Processing, 2009: 109-112.
[16] Cheng Jingxing, Hou Yuqing, Dong Fang, et al.. Fluorescence molecular tomography based on the sparse regularization and adaptive finite element method[J]. Journal of Xidian University, 2015, 42(2): 174-179.
[17] Zhang Y, Zhang L, Wu Y. The augmented Lagrangian method for a type of inverse quadratic programming problems over second-order cones[J]. TOP, 2014, 22(1): 45-79.
[18] Ghadimi E, Teixeira A, Shames I, et al.. Optimal parameter selection for the alternating direction method of multipliers (ADMM): Quadratic problems[J]. IEEE Transactions on Automatic Control, 2015, 60(3): 644-658.
[19] Eckstein J, Bertsekas D P. On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators [J]. Mathematical Programming, 1992, 55(1-3): 293-318.
