M. A. Pereyra, N. Dobigeon, H. Batatia, and J. Tourneret, Segmentation of skin lesions in 2D and 3D ultrasound images using a spatially coherent generalized Rayleigh mixture model, IEEE Transactions on Medical Imaging, vol.31, issue.8, pp.1509-1520, 2012.

O. Bernard, J. , and D. Friboulet, Statistics of the radio-frequency signal based on K distribution with application to echocardiography, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol.53, issue.9, pp.1689-1694, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01919949

M. Alessandrini, S. Maggio, J. Porée, L. De-marchi, N. Speciale et al., A restoration framework for ultrasonic tissue characterization, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol.58, issue.11, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00688924

J. A. Jensen, J. Mathorne, T. Gravesen, and B. Stage, Deconvolution of in-vivo ultrasound B-mode images, Ultrasonic Imaging, vol.15, issue.2, pp.122-133, 1993.

J. Ng, R. Prager, N. Kingsbury, G. Treece, and A. Gee, Modeling ultrasound imaging as a linear, shift-variant system, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol.53, issue.3, pp.549-563, 2006.

N. Zhao, A. Basarab, D. Kouamé, and J. Tourneret, Joint segmentation and deconvolution of ultrasound images using a hierarchical Bayesian model based on generalized Gaussian priors, IEEE Transactions on Image Processing, vol.25, issue.8, pp.3736-3750, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01374064

J. A. Jensen, Deconvolution of ultrasound images, Ultrasonic imaging, vol.14, issue.1, pp.1-15, 1992.

O. Michailovich and A. Tannenbaum, Blind deconvolution of medical ultrasound images: A parametric inverse filtering approach, IEEE Transactions on Image Processing, vol.16, issue.12, pp.3005-3019, 2007.

H. Ayasso and A. Mohammad-djafari, Joint NDT image restoration and segmentation using Gauss-Markov-Potts prior models and variational Bayesian computation, IEEE Transactions on Image Processing, vol.19, issue.9, pp.2265-2277, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00494945

A. Pirayre, Y. Zheng, L. Duval, and J. Pesquet, HOGMep: Variational Bayes and higher-order graphical models applied to joint image recovery and segmentation, 2017 IEEE International Conference on Image Processing, pp.3775-3779, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01862840

M. Pereyra, P. Schniter, E. Chouzenoux, J. Pesquet, J. Tourneret et al., A survey of stochastic simulation and optimization methods in signal processing, IEEE Journal of Selected Topics in Signal Processing, vol.10, issue.2, pp.224-241, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01312917

R. M. Neal, Handbook of Markov Chain Monte Carlo, vol.2, 2011.

C. P. Robert, V. Elvira, N. Tawn, and C. Wu, Accelerating MCMC algorithms, Wiley Interdisciplinary Reviews: Computational Statistics, vol.10, issue.5, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01961128

A. Durmus, E. Moulines, and M. Pereyra, Efficient Bayesian computation by proximal Markov chain Monte Carlo: when Langevin meets Moreau, SIAM Journal on Imaging Sciences, vol.11, issue.1, pp.473-506, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01267115

M. Pereyra, Proximal Markov chain Monte Carlo algorithms, Statistics and Computing, vol.26, issue.4, pp.745-760, 2016.

A. Schreck, G. Fort, S. L. Corff, and E. Moulines, A shrinkage-thresholding Metropolis adjusted Langevin algorithm for Bayesian variable selection, IEEE Journal of Selected Topics in Signal Processing, vol.10, issue.2, pp.366-375, 2016.
URL : https://hal.archives-ouvertes.fr/hal-00921130

H. H. Bauschke and P. L. Combettes, Convex analysis and monotone operator theory in Hilbert spaces, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01517477

P. L. Combettes and J. Pesquet, Proximal splitting methods in signal processing," in Fixed-point algorithms for inverse problems in science and engineering, pp.185-212, 2011.

A. M. Stuart, J. Voss, and P. Wilberg, Conditional path sampling of SDEs and the Langevin MCMC method, Communications in Mathematical Sciences, vol.2, issue.4, pp.685-697, 2004.

E. Chouzenoux, J. Pesquet, and A. Repetti, Variable metric forward-backward algorithm for minimizing the sum of a differentiable function and a convex function, Journal of Optimization Theory and Applications, vol.162, issue.1, pp.107-132, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00789970

P. L. Combettes, D. D?ng, and B. C. V?, Proximity for sums of composite functions, Journal of Mathematical Analysis and applications, vol.380, issue.2, pp.680-688, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00643804

Y. Marnissi, E. Chouzenoux, A. Benazza-benyahia, and J. Pesquet, Majorize-minimize adapted Metropolis-Hastings algorithm, p.1909153, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01909153

G. O. Roberts and O. Stramer, Langevin diffusions and Metropolis-Hastings algorithms, Methodology and computing in applied probability, vol.4, issue.4, pp.337-357, 2002.

E. D. Schifano, R. L. Strawderman, and M. T. Wells, Majorization-minimization algorithms for nonsmoothly penalized objective functions, Electronic Journal of Statistics, vol.4, pp.1258-1299, 2010.

C. Chaux, P. L. Combettes, J. Pesquet, and V. R. Wajs, A variational formulation for frame-based inverse problems, Inverse Problems, vol.23, issue.4, pp.1495-1518, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00621883

J. A. Jensen, Simulation of advanced ultrasound systems using Field II, 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.636-639, 2004.

N. Otsu, A threshold selection method from gray-level histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979.

S. Mallat, A wavelet tour of signal processing, 1999.

X. Cai, R. Chan, M. Nikolova, and T. Zeng, A three-stage approach for segmenting degraded color images: Smoothing, lifting and thresholding (SLaT), Journal of Scientific Computing, vol.72, issue.3, pp.1313-1332, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01158169

S. Becker and J. Fadili, A quasi-Newton proximal splitting method, Advances in Neural Information Processing Systems, pp.2618-2626, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00710900

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.

S. Krishnan, K. W. Rigby, and M. , Improved estimation of phase aberration profiles, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol.44, issue.3, pp.701-713, 1997.

P. L. Combettes and V. Wajs, Signal recovery by proximal forward-backward splitting, Multiscale Modeling & Simulation, vol.4, issue.4, pp.1168-1200, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00017649

N. Pustelnik and L. Condat, Proximity operator of a sum of functions; application to depth map estimation, IEEE Signal Processing Letters, vol.24, issue.12, pp.1827-1831, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01570182