Model-driven parameterization of fetal cortical surfaces

Surface-based analysis is a tool of choice to study the anatomy and function of the cortex in adult and children brains. Common surface registration approaches are not adaptable to fetal data since data-driven mapping techniques are limited by the lack of structural features across all gestational ages. In this work, we adapt the HIP-HOP model-driven cortical surface parameterization method to the specific problem of defining correspondences across fetuses with different gestational ages. We demonstrate the validity of our approach by quantifying the curvature evolution during development. Our findings are highly consistent with previous studies. This work is the first demonstration of the feasibility of applying surface-based mapping and analysis to fetal data.