A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

Brun, C., Leporé, N., Pennec, X., Chou, Y. Y., Lee, A. D., de Zubicaray, G., McMahon, K., Wright, M., Barysheva, M., Toga, A. W., & Thompson, P. M. (2008) A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies. In 2008 5th IEEE International Symposium on Biomedical Imaging : From Nano to Macro : Proceedings : May 14-17, 2008, Paris Marriott Rive Gauche Hotel & Conference Center, Paris, France, IEEE Engineering in Medicine and Biology Society, Paris, France, pp. 1115-1118.

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Abstract

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

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ID Code: 85690
Item Type: Conference Paper
Refereed: Yes
Keywords: Brain imaging, Genetics, MRI, Registration, Statistical analysis
DOI: 10.1109/ISBI.2008.4541196
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: 20 Jul 2015 01:34
Last Modified: 01 Sep 2015 02:44

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