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.
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Statistical Parametric Mapping, http://www.fil.ion.ucl.ac.uk/spm
Expectation Maximization Segmentation, http://www.medicalimagecomputing.com/EMS
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Murgasova, M., Dyet, L., Edwards, D., Rutherford, M., Hajnal, J.V., Rueckert, D. (2006). Segmentation of Brain MRI in Young Children. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866565_84
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