Quantifying brain development in early childhood using segmentation and registration

P. Aljabar, K. K. Bhatia, M. Murgasova, J. V. Hajnal, J. P. Boardman, L. Srinivasan, M. A. Rutherford, L. E. Dyet, A. D. Edwards, D. Rueckert

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this work we obtain estimates of tissue growth using longitudinal data comprising MR brain images of 25 preterm children scanned at one and two years. The growth estimates are obtained using segmentation and registration based methods. The segmentation approach used an expectation maximisation (EM) method to classify tissue types and the registration approach used tensor based morphometry (TBM) applied to a free form deformation (FFD) model. The two methods show very good agreement indicating that the registration and segmentation approaches can be used interchangeably. The advantage of the registration based method, however, is that it can provide more local estimates of tissue growth. This is the first longitudinal study of growth in early childhood, previous longitudinal studies have focussed on later periods during childhood.

Original languageEnglish
Title of host publicationMedical Imaging 2007
Subtitle of host publicationImage Processing
EditionPART 1
StatePublished - 2007
Externally publishedYes
EventMedical Imaging 2007: Image Processing - San Diego, CA, United States
Duration: 18 Feb 200720 Feb 2007

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 1
ISSN (Print)1605-7422


ConferenceMedical Imaging 2007: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA


  • Growth
  • Registration
  • Segmentation


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