Segmentation of brain MRI in young children

Authors:
Maria Murgasova;Leigh Dyet;David Edwards;Mary Rutherford;Joseph V. Hajnal;Daniel Rueckert
Affiliations:
Visual Information Processing Group, Department of Computing, Imperial College London;Department of Imaging Sciences, Faculty of Medicine, Imperial College London;Department of Imaging Sciences, Faculty of Medicine, Imperial College London;Department of Imaging Sciences, Faculty of Medicine, Imperial College London;Department of Imaging Sciences, Faculty of Medicine, Imperial College London;Visual Information Processing Group, Department of Computing, Imperial College London
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2006

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Abstract

This paper describes an automatic tissue segmentation algorithm for brain MRI of young children. Existing segmentation methods developed for the adult brain do not take into account the specific tissue properties present in the brain MRI of young children. We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the young child brain MRI. We develop a method of creation of a population-specific atlas from young children using a single manual segmentation. The method is based on non-linear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. Using this approach we significantly improve the performance of the popular EM segmentation algorithm on brain MRI of young children.