Neuroimaging at the group level requires spatial normalization across individuals. This issue has been receiving considerable attention from multiple research groups. Here we suggest a surface-based geometric approach that consists in matching a set of cortical surfaces through their sulcal imprints. We provide the proof-of-concept of this approach by showing 1) how sulci may be automatically identified and simplified from Tl-weighted MRI data series, and 2) how this sulcal information may be considered as landmarks for recent measure-based diffeomorphic deformation approaches. In our framework, the resulting 3D transforms are naturally applied to the entire cortical surface and MRI volumes.
['Guillaume Auzias', 'Joan Alexis Glaunès', 'Arnaud Cachia', 'Pascal Cathier', 'Eric Bardinet', 'Olivier Colliot', 'Jean-François Mangin', 'Alain Trouvé', 'Sylvain Baillet']
Multi-scale diffeomorphic cortical registration under manifold sulcal constraints