A Digital Pediatric Brain Structure Atlas from T1-Weighted MR Images
Human brain atlases are indispensable tools in model-based segmentation and quantitative analysis of brain structures. However, adult brain atlases do not adequately represent the normal maturational patterns of the pediatric brain, and the use of an adult model in pediatric studies may introduce substantial bias. Therefore, we proposed to develop a digital atlas of the pediatric human brain in this study. The atlas was constructed from T1-weighted MR data set of a 9-year old, right-handed girl. Furthermore, we extracted and simplified boundary surfaces of 25 manually defined brain structures (cortical and subcortical) based on surface curvature. We constructed a 3D triangular mesh model for each structure by triangulation of the structure’s reference points. Kappa statistics (cortical, 0.97; subcortical, 0.91) indicated substantial similarities between the mesh-defined and the original volumes. Our brain atlas and structural mesh models (www.stjude.org/brainatlas) can be used to plan treatment, to conduct knowledge and model-driven segmentation, and to analyze the shapes of brain structures in pediatric patients.
Unable to display preview. Download preview PDF.
- 2.Pommert, A., Riemer, M., Schiemann, T., et al.: Knowledge-Based and 3D Imaging-Systems in Medical-Education. Information Processing 1994, vol. II, IFIP Trans A-Computer Sci. and Tech. 52, 525–532 (1994)Google Scholar
- 11.Carpenter, M.B.: Core text of neuroanatomy, 3rd edn. Williams & Wilkins, Baltimore (1985)Google Scholar
- 14.Berg, D.M., Kreveld van, M., Overmars, M., et al.: Computational geometry: algorithms and applications, 2nd rev. edn. Springer, Berlin (2000)Google Scholar
- 15.Shan, Z.Y., Parra, C., Ji, Q., Jain, J., Reddick, W.E.: A Knowledge-Guided Active Model Method of Cortical Structure Segmentation on Pediatric MR images. J. Magn. Reson. Imging (in press)Google Scholar