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Stochastic algorithm for Bayesian mixture effect template estimation

Stéphanie Allassonnière;  Estelle Kuhn — 2010

ESAIM: Probability and Statistics

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 , (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 ...

Statistical models for deformable templates in image and shape analysis

Stéphanie Allassonnière;  Jérémie Bigot;  Joan Alexis Glaunès;  Florian Maire;  Frédéric J.P. Richard — 2013

Annales mathématiques Blaise Pascal

High dimensional data are more and more frequent in many application fields. It becomes particularly important to be able to extract meaningful features from these data sets. Deformable template model is a popular way to achieve this. This paper is a review on the statistical aspects of this model as well as its generalizations. We describe the different mathematical frameworks to handle different data types as well as the deformations. We recall the theoretical convergence properties of the estimators...

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