Cortical surface alignment using geometry driven multispectral optical flow

Spatial normalization is frequently used to map data to a standard coordinate system by removing inter-subject morphological differences, thereby allowing for group analysis to be carried out. In this paper, we analyze the geometry of the cortical surface using two shape measures that are the key to distinguish sulcal and gyral regions from each other. Then a multispectral optical flow (OF) warping procedure that aims to align the shape measure maps of an atlas and a subject brain's normalized maps is described. The variational problem to estimate the OF field is solved using a Euclidean framework. After warping one brain given the OF result, we obtain a better structural and functional alignment across multiple brains.