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.