A digital pediatric brain structure atlas from T1-weighted MR images

Shan, Zuyao Y., Parra, Carlos, Ji, Qing, Ogg, Robert J., Zhang, Yong, Laningham, Fred H. and Reddick, Wilburn E. (2006). A digital pediatric brain structure atlas from T1-weighted MR images. In: Rasmus Larsen, Mads Nielsen and Jon Sporring, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2006: Proceedings, part II. 9th International Conference on Computing and Computer-Assisted Intervention (MICCAI 2006), Copenhagen, Denmark, (332-339). 1-6 October 2006. doi:10.1007/11866763_41


Author Shan, Zuyao Y.
Parra, Carlos
Ji, Qing
Ogg, Robert J.
Zhang, Yong
Laningham, Fred H.
Reddick, Wilburn E.
Title of paper A digital pediatric brain structure atlas from T1-weighted MR images
Conference name 9th International Conference on Computing and Computer-Assisted Intervention (MICCAI 2006)
Conference location Copenhagen, Denmark
Conference dates 1-6 October 2006
Proceedings title Medical Image Computing and Computer-Assisted Intervention - MICCAI 2006: Proceedings, part II   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2006
Sub-type Fully published paper
DOI 10.1007/11866763_41
ISBN 9783540447276
354044727X
ISSN 0302-9743
1611-3349
Editor Rasmus Larsen
Mads Nielsen
Jon Sporring
Volume 4191
Start page 332
End page 339
Total pages 8
Language eng
Abstract/Summary 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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

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