Segmentation of Brain MRI in Young Children

RATIONALE AND OBJECTIVES This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children. MATERIALS AND METHODS We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the brain MRI in young children. We develop a method of creation of a population-specific atlas in young children using a single manual segmentation. The method is based on nonlinear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. RESULTS Using this approach, we significantly improve the performance of the popular expectation-maximization algorithm on brain MRI in young children. The method can be used for building probabilistic atlases with any number of structures. We compare resulting algorithm with nonrigid registration-based label propagation. CONCLUSIONS Finally, both methods are used to measure the volume of seven brain structures and measure the growth between 1 and 2 years of age.