A.H. and R.A. contributed equally to this work.
Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe
Article first published online: 30 MAY 2003
Copyright © 2003 Wiley-Liss, Inc.
Human Brain Mapping
Volume 19, Issue 4, pages 224–247, August 2003
How to Cite
Hammers, A., Allom, R., Koepp, M. J., Free, S. L., Myers, R., Lemieux, L., Mitchell, T. N., Brooks, D. J. and Duncan, J. S. (2003), Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum. Brain Mapp., 19: 224–247. doi: 10.1002/hbm.10123
- Issue published online: 30 MAY 2003
- Article first published online: 30 MAY 2003
- Manuscript Accepted: 13 FEB 2003
- Manuscript Received: 17 JUN 2002
- National Society for Epilepsy
- Faculty of Medicine, Imperial College
- Medical Research Council
- Deutsche Forschungsgemeinschaft. Grant Number: HA 3013/1-1
- brain mapping;
- image processing, computer-assisted;
- anatomy, cross-sectional
Probabilistic atlases of neuroanatomy are more representative of population anatomy than single brain atlases. They allow anatomical labeling of the results of group studies in stereotaxic space, automated anatomical labeling of individual brain imaging datasets, and the statistical assessment of normal ranges for structure volumes and extents. No such manually constructed atlas is currently available for the frequently studied group of young adults. We studied 20 normal subjects (10 women, median age 31 years) with high-resolution magnetic resonance imaging (MRI) scanning. Images were nonuniformity corrected and reoriented along both the anterior-posterior commissure (AC–PC) line horizontally and the midsagittal plane sagittally. Building on our previous work, we have expanded and refined existing algorithms for the subdivision of MRI datasets into anatomical structures. The resulting algorithm is presented in the Appendix. Forty-nine structures were interactively defined as three-dimensional volumes-of-interest (VOIs). The resulting 20 individual atlases were spatially transformed (normalized) into standard stereotaxic space, using SPM99 software and the MNI/ICBM 152 template. We evaluated volume data for all structures both in native space and after spatial normalization, and used the normalized superimposed atlases to create a maximum probability map in stereotaxic space, which retains quantitative information regarding inter-subject variability. Its potential applications range from the automatic labeling of new scans to the detection of anatomical abnormalities in patients. Further data can be extracted from the atlas for the detailed analysis of individual structures. Hum. Brain Mapping 19:224–247,2003. ©2003 Wiley-Liss,Inc.