[1] Ntziachristos V, Tung C H, Bremer C, et al.. Fluorescence molecular tomography resolves protease activity in vivo[J]. Nature Medicine, 2002, 8(7): 757-761.
[2] Deliolanis N, Lasser T, Hyde D, et al.. Free-space fluorescence molecular tomography utilizing 360o geometry projections[J]. Optics Letters, 2007, 32(4): 382-384.
[3] Bai J, Xu Z. Fluorescence Molecular Tomography[M]. Berlin: Springer Berlin Heidelberg, 2013: 185-216.
[4] Ale A, Ermolayev V, Herzog E, et al.. FMT-XCT: In vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography[J]. Nature Methods, 2012, 9(6): 615-620.
[5] Xu Z, Bai J. Analysis of finite-element-based methods for reducing the ill-posedness in the reconstruction of fluorescence molecular tomography[J]. Progress in Natural Science, 2009, 19(4): 501-509.
[6] Ale A, Schulz R B, Sarantopoulos A, et al.. Imaging performance of a hybrid X-ray computed tomography -fluorescence molecular tomography system using priors[J]. Medical Physics, 2010, 37(5): 1976-1986.
[7] Bangerth W, Joshi A. Adaptive finite element methods for the solution of inverse problems in optical tomography[J]. Inverse Problems, 2008, 24(3): 034011.
[8] Donoho D L. For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution[J]. Communications on Pure and Applied Mathematics, 2006, 59(6): 797-829.
[9] Zhang Q, Qu X, Chen D, et al.. Experimental three-dimensional bioluminescence tomography reconstruction using the lp regularization [J]. Advanced Science Letters, 2012, 16(1): 125-129.
[10] Baritaux J C, Hassler K, Unser M. An efficient numerical method for general regularization in fluorescence molecular tomography [J]. IEEE Transactions on Medical Imaging, 2010, 29(4): 1075-1087.
[11] He X, Liang J, Wang X, et al.. Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method[J]. Optics Express, 2010, 18(24): 24825-24841.
[12] Xue Z, Ma X, Zhang Q, et al.. Adaptive regularized method based on homotopy for sparse fluorescence tomography[J]. Applied Optics, 2013, 52(11): 2374-2384.
[13] Yi H, Chen D, Li W, et al.. Reconstruction algorithms based on l1-norm and l2-norm for two imaging models of fluorescence molecular tomography: A comparative study[J]. Journal of Biomedical Optics, 2013, 18(5): 056013.
[14] Chartrand R. Exact reconstruction of sparse signals via nonconvex minimization[J]. IEEE Signal Processing Letters, 2007, 14(10): 707-710.
[15] Xu Z B. Data modeling: Visual psychology approach and L1/2 regularization theory[C]. Proceedings of the International Congress of Mathmaticians, 2010: 3151-3184.
[16] Chen X, Yang D, Zhang Q, et al.. L1/2 regularization based numerical method for effective reconstruction of bioluminescence tomography [J]. Journal of Applied Physics, 2014, 115(18): 184702.
[17] Zhao L, Yang H, Cong W, et al.. Compressive sensing for early time-gate reconstruction in time-domain fluorescence molecular tomography[C]. Biomedical Optics, Optical Society of America, 2014: BM3A. 37.
[18] Zhu D, Li C. Nonconvex regularizations in fluorescence molecular tomography for sparsity enhancement [J]. Physics in Medicine and Biology, 2014, 59(12): 2901.
[19] Cong A, Wang G. A finite-element-based reconstruction method for 3D fluorescence tomography[J]. Optics Express, 2005, 13(24): 9847-9857.
[20] Asif M S, Romberg J. Sparse recovery of streaming signals using L1-homotopy[J]. IEEE Transactions on Signal Processing, 2013, 62(16): 4209-4223.
[21] Guo H, Hou Y, He X, et al.. Adaptive hp finite element method for fluorescence molecular tomography with simplified spherical harmonics approximation[J]. Journal of Innovative Optical Health Sciences, 2014, 7(2): 1350057.
