Multi-contrast multi-scale surface registration for improved alignment of cortical areas

Christine Lucas Tardif, Andreas Schäfer, Miriam Waehnert, Juliane Dinse, Robert Turner, Pierre Louis Bazin

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


The position of cortical areas can be approximately predicted from cortical surface folding patterns. However, there is extensive inter-subject variability in cortical folding patterns, prohibiting a one-to-one mapping of cortical folds in certain areas. In addition, the relationship between cortical area boundaries and the shape of the cortex is variable, and weaker for higher-order cortical areas. Current 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 to improve the alignment of cortical areas. In this article, we present a new symmetric diffeomorphic multi-contrast multi-scale surface registration (MMSR) technique that works with partially inflated surfaces in the level-set framework. MMSR generates a more precise alignment of cortical surface curvature in comparison to two widely recognized surface registration algorithms. The resulting overlap in gyrus labels is comparable to FreeSurfer. Most importantly, MMSR improves the alignment of cortical areas further by including T1 maps. As a first application, we present a group average T1 map at a uniquely high-resolution and multiple cortical depths, which reflects the myeloarchitecture of the cortex. MMSR can also be applied to other MR contrasts, such as functional and connectivity data.

Original languageEnglish (US)
Pages (from-to)107-122
Number of pages16
StatePublished - May 1 2015


  • Cortical alignment
  • Multi-contrast
  • Myeloarchitecture
  • Surface registration
  • Symmetric diffeomorphic transformation
  • T1

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience


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