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用于改善皮质区域对齐的多对比度多尺度表面配准

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

作者信息

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

机构信息

Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

出版信息

Neuroimage. 2015 May 1;111:107-22. doi: 10.1016/j.neuroimage.2015.02.005. Epub 2015 Feb 9.

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.

摘要

皮质区域的位置可根据皮质表面折叠模式大致预测。然而,个体间皮质折叠模式存在广泛差异,这使得某些区域的皮质折叠无法进行一一映射。此外,皮质区域边界与皮质形状之间的关系是可变的,对于高阶皮质区域而言这种关系更为薄弱。例如,当前的表面配准技术利用脑沟标志或皮质曲率来对齐皮质折叠模式。因此,通过这些技术对皮质区域进行对齐本质上受到仅使用几何相似性度量的限制。磁共振成像T1图显示了反映髓鞘含量的皮质内对比度,因此可用于改善皮质区域的对齐。在本文中,我们提出了一种新的对称微分同胚多对比度多尺度表面配准(MMSR)技术,该技术在水平集框架中处理部分膨胀的表面。与两种广泛认可的表面配准算法相比,MMSR能更精确地对齐皮质表面曲率。由此产生的脑回标签重叠与FreeSurfer相当。最重要的是,MMSR通过纳入T1图进一步改善了皮质区域的对齐。作为首个应用,我们展示了一个具有独特高分辨率和多个皮质深度的群体平均T1图,它反映了皮质的髓鞘结构。MMSR还可应用于其他磁共振对比度,如功能和连接性数据。

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