Paper
10 March 2006 A pediatric brain structure atlas from T1-weighted MR images
Zuyao Y. Shan, Carlos Parra, Qing Ji, Robert J. Ogg, Yong Zhang, Fred H. Laningham, Wilburn E. Reddick
Author Affiliations +
Abstract
In this paper, we have developed a digital atlas of the pediatric human brain. Human brain atlases, used to visualize spatially complex structures of the brain, 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. Higher curvature surfaces were simplified with more reference points; lower curvature surfaces, with fewer. 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 modeldriven segmentation, and to analyze the shapes of brain structures in pediatric patients.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zuyao Y. Shan, Carlos Parra, Qing Ji, Robert J. Ogg, Yong Zhang, Fred H. Laningham, and Wilburn E. Reddick "A pediatric brain structure atlas from T1-weighted MR images", Proc. SPIE 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, 614126 (10 March 2006); https://doi.org/10.1117/12.651922
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KEYWORDS
Brain

Magnetic resonance imaging

Neuroimaging

Image segmentation

3D modeling

Visualization

Shape analysis

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