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Abstract #4695

Non-Rigid Registration of T1 MR Images Constrained with Fractional Anisotropic (FA) Maps

Xia Li1, Benoit Dawant2, Xin Hong1, Zhaohua Ding1, John Gore1, Adam Anderson1

1Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; 2Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA


Conventional T1 or T2 weighted MR images provide basic contrast information for brains. However, those images are limited because they provide little contrast between distinct white matter structures. Diffusion tensor imaging (DTI) is a complementary tool that provides information on the orientation and integrity of white matter fiber bundles. The co-registration of intra- or inter-subject DTI data in a standard coordinate space allows us to perform statistical analysis of DTI images, or compare data across subjects. In this study, a non-rigid registration algorithm, which combines both T1 weighted MR images and DTI information, is proposed, in order to retain both MR information and the significant micro-structural information about tissues.

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