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Construction of 4D infant cortical surface atlases with sharp folding patterns via spherical patch‐based group‐wise sparse representation

机译:通过基于球形补丁的分组稀疏表示构造具有清晰折叠模式的4D婴儿皮质表面地图集

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摘要

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.
机译:理解动态早期大脑发育非常需要覆盖密集时间点的4D(时空+时空)婴儿皮质表面图集。在本文中,我们构建了一组4D婴儿皮质表面图集,这些图集在出生后的前六个年中的11个时间点,即在1、3、6、9、12、18、24处具有纵向一致且清晰的皮质属性模式,36、48、60和72个月大,旨在更好地使动态变化的早期大脑皮质表面正常化。为了确保纵向一致性和无偏性,我们采用了两阶段的逐组表面配准。为了在地图集上保留清晰的皮层属性模式,而不是简单地对共同注册的皮层表面进行平均,我们利用增强字典利用基于球面补丁的稀疏表示来克服潜在的注册错误。我们的地图集不仅提供了皮质折叠的几何属性,而且还提供了皮质厚度和髓磷脂含量。因此,为了解决图集上不同皮质属性的一致性,而不是稀疏地独立表示每个属性,我们联合使用组稀疏性约束来表示所有皮质属性。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小块,即FreeSurfer小块和多峰小块。与使用其他方法构造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,因此可提高单个婴儿皮质表面到该图谱的配准准确性。

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