Intrinsic and Extrinsic Analysis on Computational Anatomy

Abstract : We present intrinsic and extrinsic methods for studying anatomical coordinates in order to perform statistical inference on random physiological signals F across clinical populations. To do so, we introduce generalized partition functions of the coordinates, (x), x 2 M, which are used to construct a random field model of F on M. In the intrinsic analysis, such partition functions are defined intrinsically for individual anatomical coordinate based on Courant's theorem on nodal analysis via self adjoint operators. On the contrary to the intrinsic method, the extrinsic method needs only one set of partition functions for a template coordinate system, and then applied to each anatomical coordinate system via transformation. For illustration, we give clinical studies on cortical thickness for each of these methods.
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Communication dans un congrès
Xavier Pennec and Sarang Joshi. 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Oct 2006, Copenhagen, Denmark. pp.68-79, 2006
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Dernière modification le : mercredi 26 octobre 2011 - 12:55:49
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  • HAL Id : inria-00635889, version 1

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Anqi Qiu, Laurent Younes, Michael I Miller. Intrinsic and Extrinsic Analysis on Computational Anatomy. Xavier Pennec and Sarang Joshi. 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Oct 2006, Copenhagen, Denmark. pp.68-79, 2006. 〈inria-00635889〉

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