Name
Abstract | ||
|---|---|---|
Joint deconvolution and segmentation of ultrasound images is a challenging problem in medical imaging. By adopting a hierarchical Bayesian model, we propose 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 precondit... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LSP.2019.2935610 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Image segmentation,Ultrasonic imaging,Deconvolution,Bayes methods,Markov processes,Monte Carlo methods,Signal processing algorithms | Convergence (routing),Bayesian inference,Markov chain Monte Carlo,Pattern recognition,Segmentation,Medical imaging,Hybrid Monte Carlo,Deconvolution,Minification,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 10 | 1070-9908 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marie-Caroline Corbineau | 1 | 4 | 1.42 |
| Denis Kouame | 2 | 52 | 13.89 |
| Emilie Chouzenoux | 3 | 202 | 26.37 |
| Jean-Yves Tourneret | 4 | 1154 | 104.46 |
| Jean-Christophe Pesquet | 5 | 18 | 11.52 |