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Non-linear local registration of functional data

Isabelle Corouge 1 Christian Barillot 1 Pierre Hellier 1 Pierre Toulouse 2 Bernard Gibaud 2 
1 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Within the scope of three-dimensional brain imaging we propose an inter-individual fusion scheme to register functional activations relatively to anatomical cortical structures, the sulci. This approach is local and non-linear. It relies on a statistical sulci shape model accounting for the inter-individual variability of a population of subjects, and providing deformation modes relatively to a reference shape (a mean sulcus). The deformation field obtained between a given sulcus and the reference sulcus is extended to a neighborhood of the given sulcus by using the thin-plate spline interpolation. It is then applied to the functional activations associated with this sulcus. This approach is compared with other classical matching methods.
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Submitted on : Friday, January 11, 2013 - 3:53:04 PM
Last modification on : Friday, February 4, 2022 - 3:30:45 AM

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Isabelle Corouge, Christian Barillot, Pierre Hellier, Pierre Toulouse, Bernard Gibaud. Non-linear local registration of functional data. Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2001, Netherlands. pp.948-956, ⟨10.1007/3-540-45468-3_113⟩. ⟨inserm-00773104⟩



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