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EN FR
OPIS - 2019
Overall Objectives
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Bibliography


Section: New Results

Preconditioned P-ULA for Joint Deconvolution-Segmentation of Ultrasound Images

Participants: Emilie Chouzenoux, Marie-Caroline Corbineau, Jean-Christophe Pesquet (Collaboration: Denis Kouamé, Jean-Yves Tourneret, IRIT, Toulouse)

Joint deconvolution and segmentation of ultrasound images is a challenging problem in medical imaging. By adopting a hierarchical Bayesian model, we propose in [15] an accelerated Markov chain Monte Carlo scheme where the tissue reflectivity function is sampled thanks to a recently introduced proximal unadjusted Langevin algorithm. This new approach is combined with a forward-backward step and a preconditioning strategy to accelerate the convergence, and with a method based on the majorization-minimization principle to solve the inner nonconvex minimization problems. As demonstrated in numerical experiments conducted on both simulated and in vivo ultrasound images, the proposed method provides high-quality restoration and segmentation results and is up to six times faster than an existing Hamiltonian Monte Carlo method.