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Conference Paper

Multi-modal surface-based alignment of cortical areas using intra-cortical T1 contrast

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Tardif,  Christine
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Dinse,  Juliane
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Faculty of Computer Science, Otto von Guericke University Magdeburg, Germany;

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Schäfer,  Andreas
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Turner,  Robert
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Bazin,  Pierre-Louis
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Tardif, C., Dinse, J., Schäfer, A., Turner, R., & Bazin, P.-L. (2013). Multi-modal surface-based alignment of cortical areas using intra-cortical T1 contrast. In L. Shen, T. Liu, P.-T. Yap, H. Huang, D. Shen, & C.-F. Westin (Eds.), Multimodal brain image analysis (pp. 222-232). Berlin: Springer. doi:10.1007/978-3-319-02126-3_22.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-4F5F-5
Abstract
The position of cortical areas in the brain is related to cortical folding patterns; however, intersubject variability remains, particularly for higher cortical areas. Current cortical surface registration techniques align cortical folding patterns using sulcal landmarks or cortical curvature, for instance. The alignment of cortical areas by these techniques is thus inherently limited by the sole use of geometric similarity metrics. Magnetic resonance imaging T1 maps show intra-cortical contrast that reflects myelin content, and thus can be used, in addition to cortical geometry, to improve the alignment of cortical areas. In this article, we present a new symmetric diffeomorphic multi-modal surface-based registration technique that works in the level-set framework. We demonstrate that the alignment of cortical areas is improved by using T1 maps. Finally, we present a unique group-average ultra-high resolution T1 map at multiple cortical depths, highlighting the registration accuracy achieved. The method can easily be extended to include other MR contrasts, such as functional data and anatomical connectivity, as well as other neuroimaging modalities.