MAP Estimation of Statistical Deformable Templates Via Nonlinear Mixed Effects Models : Deterministic and Stochastic Approaches

Abstract : In [1], a new coherent statistical framework for estimating statistical deformable templates relevant to computational anatomy (CA) has been proposed. This paper addresses the problem of population av- erage and estimation of the underlying geometrical variability as a MAP computation problem for which deterministic and stochastic approxima- tion schemes have been proposed. We illustrate some of the numerical issues with handwritten digit and 2D medical images and apply the es- timated models to classification through maximum likelihood.
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Communication dans un congrès
Xavier Pennec. 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Oct 2008, New-York, United States. pp.80-91, 2008
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  • HAL Id : inria-00632876, version 1

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Stéphanie Allassonnière, Estelle Kuhn, Alain Trouvé. MAP Estimation of Statistical Deformable Templates Via Nonlinear Mixed Effects Models : Deterministic and Stochastic Approaches. Xavier Pennec. 2nd MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Oct 2008, New-York, United States. pp.80-91, 2008. 〈inria-00632876〉

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