MAP Estimation of Statistical Deformable Templates Via Nonlinear Mixed Effects Models : Deterministic and Stochastic Approaches
نویسندگان
چکیده
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 average and estimation of the underlying geometrical variability as a MAP computation problem for which deterministic and stochastic approximation schemes have been proposed. We illustrate some of the numerical issues with handwritten digit and 2D medical images and apply the estimated models to classification through maximum likelihood.
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