M. Bertero, C. D. Mol, and E. R. Pike, Linear inverse problems with discrete data: II. Stability and regularisation, Inverse Problems, vol.4, issue.3, pp.573-594, 1988.
DOI : 10.1088/0266-5611/4/3/004

W. F. Cheong, S. A. Prahl, and A. J. Welch, A review of the optical properties of biological tissues, IEEE Journal of Quantum Electronics, vol.26, issue.12, pp.2166-2185, 1990.
DOI : 10.1109/3.64354

J. P. Culver, R. Choe, M. J. Holboke, L. Zubkov, T. Durduran et al., Three-dimensional diffuse optical tomography in the parallel plane transmission geometry: Evaluation of a hybrid frequency domain/continuous wave clinical system for breast imaging, Medical Physics, vol.40, issue.2, pp.235-247, 2003.
DOI : 10.1118/1.1534109

N. Ducros, A. D. Silva, J. Dinten, and F. Peyrin, A comprehensive study of the use of temporal moments in time-resolved diffuse optical tomography: part I. Theoretical material, Physics in Medicine and Biology, vol.54, issue.23, 2009.
DOI : 10.1088/0031-9155/54/23/004
URL : https://hal.archives-ouvertes.fr/hal-00872352

N. Galatsanos and A. Katsaggelos, Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation, IEEE Transactions on Image Processing, vol.1, issue.3, pp.322-336, 1992.
DOI : 10.1109/83.148606

F. Gao, Y. Tanikawa, H. Zhao, and Y. Yamada, Semi-three-dimensional algorithm for time-resolved diffuse optical tomography by use of the generalized pulse spectrum technique, Applied Optics, vol.41, issue.34, pp.417346-7358, 2002.
DOI : 10.1364/AO.41.007346

F. Gao, H. J. Zhao, Y. Tanikawa, and Y. Yamada, A linear, featured-data scheme for image reconstruction in time-domain fluorescence molecular tomography, Optics Express, vol.14, issue.16, pp.147109-7124, 2006.
DOI : 10.1364/OE.14.007109

R. J. Gaudette, D. H. Brooks, D. Marzio, C. A. Kilmer, M. E. Miller et al., A comparison study of linear reconstruction techniques for diffuse optical tomographic imaging of absorption coefficient, Physics in Medicine and Biology, vol.45, issue.4, pp.1051-1070, 2000.
DOI : 10.1088/0031-9155/45/4/318

G. Golub, M. Heath, and G. Wahba, Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter, Technometrics, vol.5, issue.2, pp.215-223, 1979.
DOI : 10.1080/03610927508827223

E. E. Graves, J. P. Culver, J. Ripoll, R. Weissleder, N. et al., Singular-value analysis and optimization of experimental parameters in fluorescence molecular tomography, Journal of the Optical Society of America A, vol.21, issue.2, pp.231-241, 2004.
DOI : 10.1364/JOSAA.21.000231

C. Hansen, The truncatedSVD as a method for regularization, BIT, vol.13, issue.13, pp.534-553, 1987.
DOI : 10.1007/BF01937276

C. Hansen, Analysis of Discrete Ill-Posed Problems by Means of the L-Curve, SIAM Review, vol.34, issue.4, pp.561-580, 1992.
DOI : 10.1137/1034115

D. Hyde, E. Miller, D. Brooks, N. , and V. , A Statistical Approach to Inverting the Born Ratio, IEEE Transactions on Medical Imaging, vol.26, issue.7, pp.26893-905, 2007.
DOI : 10.1109/TMI.2007.895467

D. S. Kepshire, S. C. Davis, H. Dehghani, K. D. Paulsen, and B. W. Pogue, Subsurface diffuse optical tomography can localize absorber and fluorescent objects but recovered image sensitivity is nonlinear with depth, Applied Optics, vol.46, issue.10, pp.461669-1678, 2007.
DOI : 10.1364/AO.46.001669

M. E. Kilmer, O. Leary, and D. P. , Choosing Regularization Parameters in Iterative Methods for Ill-Posed Problems, SIAM Journal on Matrix Analysis and Applications, vol.22, issue.4, pp.1204-1221, 2001.
DOI : 10.1137/S0895479899345960

A. T. Kumar, S. B. Raymond, A. K. Dunn, B. J. Bacskai, and D. A. Boas, A Time Domain Fluorescence Tomography System for Small Animal Imaging, IEEE Transactions on Medical Imaging, vol.27, issue.8, pp.271152-1163, 2008.
DOI : 10.1109/TMI.2008.918341

S. Lam, F. Lesage, and X. Intes, Time Domain Fluorescent Diffuse Optical Tomography: analytical expressions, Optics Express, vol.13, issue.7, pp.2263-2275, 2005.
DOI : 10.1364/OPEX.13.002263

I. L. Medintz, H. T. Uyeda, E. R. Goldman, and H. Mattoussi, Quantum dot bioconjugates for imaging, labelling and sensing, Nature Materials, vol.45, issue.6, pp.435-446, 2005.
DOI : 10.1126/science.1104274

K. Miller, Least Squares Methods for Ill-Posed Problems with a Prescribed Bound, SIAM Journal on Mathematical Analysis, vol.1, issue.1, pp.52-74, 1970.
DOI : 10.1137/0501006

T. Nielsen, B. Brendel, R. Ziegler, M. Van-beek, F. Uhlemann et al., Linear image reconstruction for a diffuse optical mammography system in a noncompressed geometry using scattering fluid, Applied Optics, vol.48, issue.10, pp.48-49, 2009.
DOI : 10.1364/AO.48.0000D1

T. Regi´nskaregi´nska, Regularization of Discrete Ill-Posed Problems, BIT Numerical Mathematics, vol.44, issue.1, pp.119-133, 2004.
DOI : 10.1023/B:BITN.0000025090.68586.5e

J. Riley, M. Hassan, V. Chernomordik, and A. Gandjbakhche, Choice of data types in time resolved fluorescence enhanced diffuse optical tomography, Medical Physics, vol.71, issue.12, p.4890, 2007.
DOI : 10.1063/1.1287748

J. Selb, A. Dale, and D. Boas, Linear 3D reconstruction of time-domain diffuse optical imaging differential data: improved depth localization and lateral resolution, Optics Express, vol.15, issue.25, pp.1516400-16412, 2007.
DOI : 10.1364/OE.15.016400

A. N. Tikhonov and V. A. Arsenin, Solution of Ill-posed Problems, 1977.

Y. Urano, D. Asanuma, Y. Hama, Y. Koyama, T. Barrett et al., Selective molecular imaging of viable cancer cells with pH-activatable fluorescence probes, Nature Medicine, vol.69, issue.1, pp.104-109, 2009.
DOI : 10.1158/1078-0432.CCR-06-2240