Human Brain Myelination from Birth to 4.5 Years

  • Berengere Aubert-Broche
  • Vladimir Fonov
  • Ilana Leppert
  • G. Bruce Pike
  • D. Louis Collins
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)


The myelination of white matter from birth through the first years of life has been studied qualitatively and it is well know the myelination occurs in a orderly and predictable manner, proceeding in a caudocranial direction, from deep to superficial and from posterior to anterior. Even if the myelination is a continuous process, it is useful to characterize myelination evolution in normal brain development in order to better study demyelinating diseases. The quantification of myelination has only been studied for neonates. The original contribution of this study is to develop a method to characterize and visualize the myelination pattern using MRI data from a group of normal subjects from birth to just over 4 years of age. The method includes brain extraction and tissue classification in addition to the analysis of T2 relaxation times to attempt to separate myelinated and unmyelinated white matter. The results agree previously published qualitative observations.


White Matter Gray Matter Normal Brain Development Central Gray Matter White Matter Voxels 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Barkovich, A., Kjos, B., et al.: Normal maturation of the neonatal and infant brain: MR imaging at 1.5 T. Radiology 166, 173–180 (1988)CrossRefGoogle Scholar
  2. 2.
    Ono, J., Kodaka, R., et al.: Evaluation of myelination by means of the T2 value on magnetic resonance imaging. Brain Dev. 15, 433–438 (1993)CrossRefGoogle Scholar
  3. 3.
    Nishida, M., Makris, N., et al.: Detailed semiautomated MRI based morphometry of the neonatal brain. Neuroimage 32, 1041–1049 (2006)CrossRefGoogle Scholar
  4. 4.
    Gilmore, J., Lin, W., et al.: Regional GM growth, sexual dimorphism, and cerebral asymmetry in the neonatal brain. J. Neurosc. 27, 1255–1260 (2007)CrossRefGoogle Scholar
  5. 5.
    Murgasova, M., Dyet, L., et al.: Segmentation of brain MRI in young children. Acad. Radiol. 14, 1350–1366 (2007)CrossRefGoogle Scholar
  6. 6.
    Evans, A.: The NIH MRI study of normal brain development. NeuroImage 30, 184–202 (2006)CrossRefGoogle Scholar
  7. 7.
    Sled, J., Zijdenbos, A., Evans, A.: A nonparametric method for automatic correction of intensity nonuniformity in MRI data. TMI 17, 87–97 (1998)Google Scholar
  8. 8.
    Coupe, P., Yger, P., et al.: An optimized blockwise non local means denoising filter for 3d magnetic resonance images. IEEE TMI (accepted, 2007)Google Scholar
  9. 9.
    Collins, D., Neelin, P., et al.: Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. In: JCAT, vol. 18, pp. 192–205 (1994)Google Scholar
  10. 10.
    Evans, A., Collins, D., et al.: 3D statistical neuroanatomical models from 305 MRI volumes. In: IEEE NSS/MIC, San Francisco, USA, pp. 1813–1817 (1993)Google Scholar
  11. 11.
    Cocosco, C., Zijdenbos, A., Evans, A.: A fully automatic and robust brain MRI tissue classification method. MIA 7, 513–527 (2003)Google Scholar
  12. 12.
    Ding, X., Kucinski, T., et al.: Normal brain maturation characterized with age-related T2 relaxation times: an attempt to develop a quantitative imaging measure for clinical use. Invest Radiol. 39, 740–746 (2004)CrossRefGoogle Scholar
  13. 13.
    Leppert, I., Almli, R., et al.: Pediatric age-related T2 relaxometry in normal brain development. In: OHBM, Florence, Italy (2006)Google Scholar
  14. 14.
    Van Der Knaap, M., Valk, J.: MR imaging of the various stages of normal myelination during the first year of life. Neurorad. 31, 459–470 (1990)CrossRefGoogle Scholar
  15. 15.
    Parazzini, C., Baldoli, C., et al.: Terminal zones of myelination: MR evaluation of children aged 20-40 months. AJNR 23, 1669–1673 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Berengere Aubert-Broche
    • 1
  • Vladimir Fonov
    • 1
  • Ilana Leppert
    • 1
  • G. Bruce Pike
    • 1
  • D. Louis Collins
    • 1
  1. 1.Montreal Neurological InstituteMcGill UniversityMontrealCanada

Personalised recommendations