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Image Registration for Distortion Correction in Diffusion Tensor Imaging

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2717))

Abstract

In diffusion tensor imaging the calculation of functional information is limited by head movement and eddy current-induced image distortion. In this paper the application of image registration for distortion correction is investigated. In particular, a 3D affine and a dedicated transformation which is adapted to the type of distortion and the similarity measures mutual information and local correlation are compared to each other. The registration results are quantitatively evaluated by analyzing their consistency properties. Visual inspection shows that registration generally improves the quality of the functional information. The consistency tests reveal that both transformations provide similar registration results which is remarkable since the dedicated transformation does not take advantage of modeling of the underlying imaging physics. Furthermore, it is shown that local correlation similarity is an interesting alternative to mutual information. The registration of a DTI series with local correlation is more consistent and takes only about one minute for calculation.

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© 2003 Springer-Verlag Berlin Heidelberg

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Netsch, T., van Muiswinkel, A. (2003). Image Registration for Distortion Correction in Diffusion Tensor Imaging. In: Gee, J.C., Maintz, J.B.A., Vannier, M.W. (eds) Biomedical Image Registration. WBIR 2003. Lecture Notes in Computer Science, vol 2717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39701-4_18

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  • DOI: https://doi.org/10.1007/978-3-540-39701-4_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20343-8

  • Online ISBN: 978-3-540-39701-4

  • eBook Packages: Springer Book Archive

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