Best individual template selection from deformation tensor minimization

Leporé, N., Brun, C., Chou, Y. Y., Lee, A. D., Barysheva, M., Pennec, X., McMahon, K. L., Meredith, M., de Zubicaray, G. I., Wright, M. J., Toga, A. W., & Thompson, P. M. (2008) Best individual template selection from deformation tensor minimization. In 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, IEEE, Paris, France.

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Abstract

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. We also computed the intraclass correlation and associated permutation p-value at each voxel for the determinant of the Jacobian matrix of the transformation. The cumulative distribution function (cdf) of the p-values was found at each voxel for each of the templates and compared to the null distribution. Surprisingly, there was very little difference between CDFs of statistics computed from analyses using different templates. As the brain with least log-Euclidean deformation cost, the mean template defined here avoids the blurring caused by creating a synthetic image from a population, and when selected from a large population, avoids bias by being geometrically centered, in a metric that is sensitive enough to anatomical similarity that it can even detect genetic affinity among anatomies.

Impact and interest:

5 citations in Scopus
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3 citations in Web of Science®

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ID Code: 85810
Item Type: Conference Paper
Refereed: Yes
Keywords: Brain, Image analysis, Magnetic resonance imaging
DOI: 10.1109/ISBI.2008.4541032
ISBN: 9781424420032
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copyright 2008 IEEE
Deposited On: 01 Sep 2015 02:09
Last Modified: 03 Sep 2015 05:21

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