Construction of 4D infant cortical surface atlases with sharp folding patterns via spherical patch-based group-wise sparse representation
Construction of 4D infant cortical surface atlases with sharp folding patterns via spherical patch-based group-wise sparse representation
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DOI：
10.1002/hbm.24636
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发表时间：
2019-09-01
影响因子：
4.8
通讯作者：
Shen, Dinggang
中科院分区：
文献类型：
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作者：
Wu, Zhengwang;Wang, Li;Shen, Dinggang
4D（空间+时间）婴儿皮层表面图谱覆盖密集的时间点是非常需要了解动态的早期大脑发育。在这篇文章中，我们构建了一组4D婴儿皮质表面图谱，在出生后的前六年的11个时间点，即1，3，6，9，12，18，24，36，48，60和72个月，这是有针对性的更好地规范化的动态变化的早期大脑皮质表面的纵向一致和尖锐的皮质属性模式。为了保证纵向一致性和无偏性，我们采用了两阶段的分组式表面配准。为了保留清晰的皮质属性模式的图集，而不是简单地平均在共配准的皮质表面，我们利用一个球形补丁为基础的稀疏表示使用增强字典，以克服潜在的配准错误。我们的图谱不仅提供了皮质折叠的几何属性，还提供了皮质厚度和髓鞘含量。因此，为了解决图谱上不同皮质属性的一致性，我们用组稀疏约束联合表示所有皮质属性，而不是独立地稀疏表示每个属性。此外，为了进一步促进使用我们的地图集进行基于区域的分析，我们还在我们的4D婴儿皮质表面地图集上提供了两种广泛使用的包裹，即FreeSurfer包裹和多模式包裹。与其他方法构建的皮质表面图谱相比，我们的皮质表面图谱保留了更清晰的皮质折叠属性模式，从而使单个婴儿皮质表面与图谱的配准精度更高。
4D (spatial + temporal) infant cortical surface atlases covering dense time points are highly needed for understanding dynamic early brain development. In this article, we construct a set of 4D infant cortical surface atlases with longitudinally consistent and sharp cortical attribute patterns at 11 time points in the first six postnatal years, that is, at 1, 3, 6, 9, 12, 18, 24, 36, 48, 60, and 72 months of age, which is targeted for better normalization of the dynamic changing early brain cortical surfaces. To ensure longitudinal consistency and unbiasedness, we adopt a two-stage group-wise surface registration. To preserve sharp cortical attribute patterns on the atlas, instead of simply averaging over the coregistered cortical surfaces, we leverage a spherical patch-based sparse representation using the augmented dictionary to overcome the potential registration errors. Our atlases provide not only geometric attributes of the cortical folding, but also cortical thickness and myelin content. Therefore, to address the consistency across different cortical attributes on the atlas, instead of sparsely representing each attribute independently, we jointly represent all cortical attributes with a group-wise sparsity constraint. In addition, to further facilitate region-based analysis using our atlases, we have also provided two widely used parcellations, that is, FreeSurfer parcellation and multimodal parcellation, on our 4D infant cortical surface atlases. Compared to cortical surface atlases constructed with other methods, our cortical surface atlases preserve sharper cortical folding attribute patterns, thus leading to better accuracy in registration of individual infant cortical surfaces to the atlas.