Abstract

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.

Highlights

  • Image registration is crucial for brain mapping studies, such as comparative morphometry and group analysis of functional data, in order to compensate for differences in position, size and shape of brain structures across individuals

  • In the previous two experiments, we showed that multi-contrast multi-scale surface registration (MMSR) outperforms FreeSurfer and Spherical Demons at aligning cortical surfaces based on their shape

  • High-resolution T1 maps acquired at 7 T show intracortical contrast that reflects the myeloarchitecture of the cortex

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Summary

Introduction

Image registration is crucial for brain mapping studies, such as comparative morphometry and group analysis of functional data, in order to compensate for differences in position, size and shape of brain structures across individuals. Many fully automated non-linear volume registration algorithms have been developed to align brain structures, and produce very good results even for strong differences due to pathology (see Klein et al (2009) for a review). These algorithms perform well for deep brain structures, they fail to accurately align the cerebral cortex, a thin sheet that is highly convoluted and variable. Surface registration driven by cortical folding patterns improves the statistical power and spatial specificity of group functional MRI analysis (Frost and Goebel, 2012; van Atteveldt et al, 2004) due to improved alignment of functional areas

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