M. Naganawa, Y. Kimura, K. Ishii, K. Oda, K. Ishiwata et al., Extraction of a plasma time-activity curve from dynamic brain PET images based on independent component analysis, IEEE Trans. Biomed. Eng, vol.52, issue.2, pp.201-210, 2005.

C. Schiepers, W. Chen, M. Dahlbom, T. Cloughesy, C. K. Hoh et al., 18F-fluorothymidine kinetics of malignant brain tumors, Eur. J. Nuclear Med. Molecular Imag, vol.34, issue.7, pp.1003-1011, 2007.

M. E. Kamasak, Computation of variance in compartment model parameter estimates from dynamic PET data, Proc. IEEE Int. Symp. Biomed. Imag. (ISBI), 2012.

R. Boellaard, A. Van-lingen, and A. A. Lammertsma, Experimental and clinical evaluation of iterative reconstruction (OSEM) in dynamic PET: Quantitative characteristics and effects on kinetic modeling, J. Nuclear Med, vol.42, issue.5, pp.808-817, 2001.

J. M. Bioucas-dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du et al., Hyperspectral unmixing overview: Geometrical, statistical, and sparse regression-based approaches, IEEE J. Sel. Topics Appl. Earth Observations Remote Sens, vol.5, issue.2, pp.354-379, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00760787

N. Dobigeon and N. Brun, Spectral mixture analysis of EELS spectrum-images, Ultramicroscopy, vol.120, pp.25-34, 2012.

J. S. Lee, D. D. Lee, S. Choi, K. S. Park, and D. S. Lee, Non-negative matrix factorization of dynamic images in nuclear medicine, IEEE Nuclear Science Symposium Conference Record, 2001.

P. Thouvenin, N. Dobigeon, and J. Tourneret, Hyperspectral unmixing with spectral variability using a perturbed linear mixing model, IEEE Trans. Signal Process, vol.64, issue.2, pp.525-538, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01273078

S. Park, N. Dobigeon, and A. O. Hero, Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM, Signal Process, vol.94, pp.386-400, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00875110

R. Tibshrani, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society, vol.58, issue.1, pp.267-288, 1996.

J. Bolte, S. Sabach, and M. Teboulle, Proximal alternating linearized minimization for nonconvex and nonsmooth problems, Mathematical Programming, vol.146, issue.1-2, pp.459-494, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00916090

L. Condat, Fast projection onto the simplex and the l 1-ball, Math. Program, vol.158, issue.1-2, pp.575-585, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01056171

S. Stute, C. Tauber, C. Leroy, M. Bottlaender, V. Brulon et al., Analytical simulations of dynamic PET scans with realistic count rates properties, IEEE Nuclear Sci. Symp. Medical Imag. Conf, pp.113-122, 2015.

J. Nascimento and J. Dias, Vertex component analysis: a fast algorithm to unmix hyperspectral data, IEEE Trans. Geosci. Remote Sens, vol.43, issue.4, pp.898-910, 2005.

J. M. Bioucas-dias and M. A. Figueiredo, Alternating direction algorithms for constrained sparse regression: Application to hyperspectral unmixing, Proc. IEEE GRSS Workshop Hyperspectral Image SIgnal Process.: Evolution in Remote Sens. (WHISPERS), 2010.