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3D Tensor Normalization for Improved Accuracy in DTI Tensor Registration Methods

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Book cover Biomedical Image Registration (WBIR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7359))

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Abstract

This paper presents a method for normalization of diffusion tensor images (DTI) to a fixed DTI template, a pre-processing step to improve the performance of full tensor based registration methods. The proposed method maps the individual tensors of the subject image in to the template space based on matching the cumulative distribution function and the fractional anisotrophy values. The method aims to determine a more accurate deformation field from any full tensor registration method by applying the registration algorithm on the normalized DTI rather than the original DTI. The deformation field applied to the original tensor images are compared to the deformed image without normalization for 11 different cases of mapping seven subjects (neonate through 2 years) to two different atlases. The method shows an improvement in DTI registration based on comparing the normalized fractional anisotropy values of major fiber tracts in the brain.

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© 2012 Springer-Verlag Berlin Heidelberg

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Gupta, A., Escolar, M., Dietrich, C., Gilmore, J., Gerig, G., Styner, M. (2012). 3D Tensor Normalization for Improved Accuracy in DTI Tensor Registration Methods. In: Dawant, B.M., Christensen, G.E., Fitzpatrick, J.M., Rueckert, D. (eds) Biomedical Image Registration. WBIR 2012. Lecture Notes in Computer Science, vol 7359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31340-0_18

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  • DOI: https://doi.org/10.1007/978-3-642-31340-0_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31339-4

  • Online ISBN: 978-3-642-31340-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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