Automatic segmentation of fetal brain using diffusion-weighted imaging cues

Abstract

Segmentation of the developing cortical plate from MRI data of the post-mortem fetal brain is highly challenging due to partial volume effects, low contrast, and heterogeneous maturation caused by ongoing myelination processes. We present a new atlas-free method that segments the inner and outer boundaries of the cortical plate in fetal brains by exploiting diffusion-weighted imaging cues and using a cortical thickness constraint. The accuracy of the segmentation algorithm is demonstrated by application to fetal sheep brain MRI data, and is shown to produce results comparable to manual segmentation and more accurate than semi-automatic segmentation.