[1] Qin C H, Feng J C, Zhu S P et al. Recent advances in bioluminescence tomography: Methodology and system as well as application[J]. Laser & Photonics Reviews, 8, 94-114(2014). http://onlinelibrary.wiley.com/doi/10.1002/lpor.201280011/full

[2] Yu J J, Zhang B, Iordachita I I et al. Systematic study of target localization for bioluminescence tomography guided radiation therapy[J]. Medical Physics, 43, 2619-2629(2016). http://onlinelibrary.wiley.com/doi/10.1118/1.4947481/pdf

[3] Han W M, Cong W X, Wang G. Mathematical theory and numerical analysis of bioluminescence tomography[J]. Inverse Problems, 22, 1659-1675(2006). http://adsabs.harvard.edu/abs/2006InvPr..22.1659H

[4] Yu J J, Wang H Y, Li Q Y. Single-view based multispectral bioluminescence tomography with iteratively shrinking permissible region[J]. Acta Optica Sinica, 36, 1211001(2016).

[5] Dehghani H, Davis S C, Pogue B W. Spectrally resolved bioluminescence tomography using the reciprocity approach[J]. Medical Physics, 35, 4836-4871(2008). http://scitation.aip.org/content/aapm/journal/medphys/35/11/10.1118/1.2982138

[6] Naser M A, Patterson M S. Algorithms for bioluminescence tomography incorporating anatomical information and reconstruction of tissue optical properties[J]. Biomedical Optics Express, 1, 512-526(2010). http://www.ncbi.nlm.nih.gov/pubmed/21258486

[7] Lu Y J, Zhang X Q, Douraghy A et al. Source reconstruction for spectrally-resolved bioluminescence tomography with sparse a priori information[J]. Optics Express, 17, 8062-8080(2009). http://pubmedcentralcanada.ca/pmcc/articles/PMC2790869/

[8] He X W, Liang J M, Wang X R et al. Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method[J]. Optics Express, 18, 24825-24841(2010). http://europepmc.org/abstract/med/21164828

[9] Donoho D L, Tsaig Y, Drori I. et al. Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 58, 1094-1121(2012). http://dl.acm.org/citation.cfm?id=2332326

[10] Hu Y F, Liu J, Leng C C et al. Lp regularization for bioluminescence tomography based on the split Bregman method[J]. Molecular Imaging and Biology, 18, 830-837(2016). http://europepmc.org/abstract/med/27277829

[11] Yu J J, Li Q Y, Wang H Y. Source reconstruction for bioluminescence tomography via L1/2 regularization[J]. Journal of Innovative Optical Health Sciences, 11, 1750014(2017). http://www.worldscientific.com/doi/abs/10.1142/S1793545817500146

[12] Chen X L, Yang D F, Zhang Q T et al. L1/2 regularization based numerical method for effective reconstruction of bioluminescence tomography[J]. Journal of Applied Physics, 115, 184702(2014). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6815924

[13] Yin P H, Lou Y F, He Q et al. Minimization of L1-2 for compressed sensing[J]. Siam Journal on Scientific Computing, 37, A536-A563(2015). http://www.researchgate.net/publication/269931830_Minimization_of_L_1-2_for_Compressed_Sensing

[14] Lou Y F, Yin P H, He Q et al. Computing sparse representation in a highly coherent dictionary based on difference of L1, and L2[J]. Journal of Scientific Computing, 64, 178-196(2015). http://link.springer.com/article/10.1007/s10915-014-9930-1

[15] Cong A X, Wang G. A finite-element-based reconstruction method for 3D fluorescence tomography[J]. Optics Express, 13, 9847-9857(2005). http://www.europepmc.org/abstract/MED/19503194

[16] Zhang H B, Geng G H, Wang X D et al[J]. Fast and robust reconstruction for fluorescence molecular tomography via L_1/2 regularization BioMed Research International, 2016, 1-9.

[17] Tao P D, le Chi H A. Convex analysis approach to DC programming: Theory, algorithms and applications[J]. Acta Mathematica Vietnamica, 22, 289-355(1997). http://www.researchgate.net/publication/310750144_Convex_analysis_approach_to_DC_programmingTheory_algorithms_and_applications

[18] Lin Z C, Liu R S, Su Z X. Linearized alternating direction method with adaptive penalty for low-rank representation[J]. Advances in Neural Information Processing Systems, 612-620(2011). http://arxiv.org/abs/1109.0367

[19] Wright S J, Nowak R D. Figueiredo M A T. Sparse reconstruction by separable approximation[J]. IEEE Transactions on Signal Processing, 57, 2479-2493(2009).

[20] Dogdas B, Stout D, Chatziioannou A F. et al. Digimouse: A 3D whole body mouse atlas from CT and cryosection data[J]. Physics in Medicine and Biology, 52, 577-587(2007). http://www.ncbi.nlm.nih.gov/pubmed/17228106

[21] He X W, Hou Y B, Chen D D et al. Sparse regularization-based reconstruction for bioluminescence tomography using a multilevel adaptive finite element method[J]. International Journal of Biomedical Imaging, 203537(2011). http://europepmc.org/articles/PMC2952815