Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia.
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
Neuroimage. 2018 Oct 1;179:11-29. doi: 10.1016/j.neuroimage.2018.06.018. Epub 2018 Jun 14.
We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The data were acquired as part of the Developing Human Connectome Project (dHCP), and the constructed surface atlases are publicly available. The method is based on a spherical registration approach: Multimodal Surface Matching (MSM), using cortical folding for driving the alignment. Templates have been generated for the anatomical cortical surface and for the cortical feature maps: sulcal depth, curvature, thickness, T1w/T2w myelin maps and cortical regions. To achieve this, cortical surfaces from 270 infants were first projected onto the sphere. Templates were then generated in two stages: first, a reference space was initialised via affine alignment to a group average adult template. Following this, templates were iteratively refined through repeated alignment of individuals to the template space until the variability of the average feature sets converged. Finally, bias towards the adult reference was removed by applying the inverse of the average affine transformations on the template and de-drifting the template. We used temporal adaptive kernel regression to produce age-dependant atlases for 9 weeks (36-44 weeks PMA). The generated templates capture expected patterns of cortical development including an increase in gyrification as well as an increase in thickness and T1w/T2w myelination with increasing age.
我们提出了一种方法,用于构建扫描时胎龄为 36 至 44 周的新生儿大脑的时空皮质表面图谱。这些数据是作为发展人类连接组计划(dHCP)的一部分获得的,构建的表面图谱是公开的。该方法基于球面对齐方法:多模态表面匹配(MSM),使用皮质折叠来驱动对齐。为解剖学皮质表面和皮质特征图生成了模板:脑沟深度、曲率、厚度、T1w/T2w 髓鞘图和皮质区域。为了实现这一点,首先将 270 名婴儿的皮质表面投影到球体上。然后分两个阶段生成模板:首先,通过仿射对齐到平均成人模板初始化参考空间。在此之后,通过将个体反复对齐到模板空间来迭代细化模板,直到平均特征集的变异性收敛。最后,通过对模板应用平均仿射变换的逆以及对模板去漂移来去除对成人参考的偏差。我们使用时间自适应核回归来生成 9 周(36-44 周 PMA)的年龄相关图谱。生成的模板捕捉到了皮质发育的预期模式,包括随着年龄的增长脑回数量的增加,以及厚度和 T1w/T2w 髓鞘化的增加。