The estimation of probabilistic deformable template models in computer vision or of probabilistic atlases in Computational Anatomy are core issues in both fields. A first coherent statistical framework where the geometrical variability is modelled as a hidden random variable has been given by [S. Allassonnière et al., J. Roy. Stat. Soc. 69 (2007) 3-29]. They introduce a bayesian approach and mixture of them to estimate deformable template models. A consistent stochastic algorithm has been introduced in [S. Allassonnière et al. (in revision)] to face the problem encountered in [S. Allassonnière et al., J. Roy. Stat. Soc. 69 (2007) 3-29] for the convergence of the estimation algorithm for the one component model in the presence of noise. We propose here to go on in this direction of using some “SAEM-like” algorithm to approximate the MAP estimator in the general bayesian setting of mixture of deformable template models. We also prove the convergence of our algorithm toward a critical point of the penalised likelihood of the observations and illustrate this with handwritten digit images and medical images.
Keywords: stochastic approximations, non rigid-deformable templates, shapes statistics, MAP estimation, bayesian method, mixture models
@article{PS_2010__14__382_0,
author = {Allassonni\`ere, St\'ephanie and Kuhn, Estelle},
title = {Stochastic algorithm for bayesian mixture effect template estimation},
journal = {ESAIM: Probability and Statistics},
pages = {382--408},
year = {2010},
publisher = {EDP Sciences},
volume = {14},
doi = {10.1051/ps/2009001},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ps/2009001/}
}
TY - JOUR AU - Allassonnière, Stéphanie AU - Kuhn, Estelle TI - Stochastic algorithm for bayesian mixture effect template estimation JO - ESAIM: Probability and Statistics PY - 2010 SP - 382 EP - 408 VL - 14 PB - EDP Sciences UR - https://www.numdam.org/articles/10.1051/ps/2009001/ DO - 10.1051/ps/2009001 LA - en ID - PS_2010__14__382_0 ER -
%0 Journal Article %A Allassonnière, Stéphanie %A Kuhn, Estelle %T Stochastic algorithm for bayesian mixture effect template estimation %J ESAIM: Probability and Statistics %D 2010 %P 382-408 %V 14 %I EDP Sciences %U https://www.numdam.org/articles/10.1051/ps/2009001/ %R 10.1051/ps/2009001 %G en %F PS_2010__14__382_0
Allassonnière, Stéphanie; Kuhn, Estelle. Stochastic algorithm for bayesian mixture effect template estimation. ESAIM: Probability and Statistics, Tome 14 (2010), pp. 382-408. doi: 10.1051/ps/2009001
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