Joshi Anand A, Li Jian, Chong Minqi, Akrami Haleh, Leahy Richard M
University of Southern California, Los Angeles, CA, USA.
Med Image Comput Comput Assist Interv. 2018 Sep;11072:198-205. doi: 10.1007/978-3-030-00931-1_23. Epub 2018 Sep 13.
Cross subject functional studies of cerebral cortex require cortical registration that aligns functional brain regions. While cortical folding patterns are approximate indicators of the underlying cytoarchitecture, coregistration based on these features alone does not accurately align functional regions in cerebral cortex. This paper presents a method for cortical surface registration (rfDemons) based on resting fMRI (rfMRI) data that uses curvature-based anatomical registration as an initialization. In contrast to existing techniques that use connectivity-based features derived from rfMRI, the proposed method uses 'synchronized' resting rfMRI time series directly. The synchronization of rfMRI data is performed using the BrainSync transform which applies an orthogonal transform to the rfMRI time series to temporally align them across subjects. The rfDemons method was applied to rfMRI from the Human Connectome Project and evaluated using task fMRI data to explore the impact of cortical registration performed using resting fMRI data on functional alignment of the cerebral cortex.
大脑皮层的跨受试者功能研究需要对功能性脑区进行皮层配准。虽然皮层折叠模式是潜在细胞结构的近似指标，但仅基于这些特征的配准并不能准确对齐大脑皮层中的功能区域。本文提出了一种基于静息态功能磁共振成像（rfMRI）数据的皮层表面配准方法（rfDemons），该方法使用基于曲率的解剖配准作为初始化。与现有使用从rfMRI导出的基于连通性特征的技术不同，该方法直接使用“同步”的静息rfMRI时间序列。rfMRI数据的同步使用BrainSync变换进行，该变换对rfMRI时间序列应用正交变换以在受试者之间进行时间对齐。将rfDemons方法应用于人类连接组计划的rfMRI，并使用任务功能磁共振成像数据进行评估，以探讨使用静息rfMRI数据进行皮层配准对大脑皮层功能对齐的影响。
