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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Corouge, I., Barillot, C., Hellier, P., Toulouse, P., Gibaud, B. (2001). Non-linear Local Registration of Functional Data. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_113
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DOI: https://doi.org/10.1007/3-540-45468-3_113
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