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Biennial International Conference on Information Processing in Medical Imaging

IPMI 2005: Information Processing in Medical Imaging pp 76–87Cite as

Maximum Entropy Spherical Deconvolution for Diffusion MRI

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3565))

Abstract

This paper proposes a maximum entropy method for spherical deconvolution. Spherical deconvolution arises in various inverse problems. This paper uses the method to reconstruct the distribution of microstructural fibre orientations from diffusion MRI measurements. Analysis shows that the PASMRI algorithm, one of the most accurate diffusion MRI reconstruction algorithms in the literature, is a special case of the maximum entropy spherical deconvolution. Experiments compare the new method to linear spherical deconvolution, used previously in diffusion MRI, and to the PASMRI algorithm. The new method compares favourably both in simulation and on standard brain-scan data.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK

    Daniel C. Alexander

Authors
  1. Daniel C. Alexander
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Iowa, IA 52242, Iowa City

    Gary E. Christensen

  2. Department of Electrical and Computer Engineering, University of Iowa, IA 52242, Iowa City, USA

    Milan Sonka

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Alexander, D.C. (2005). Maximum Entropy Spherical Deconvolution for Diffusion MRI. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_7

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  • DOI: https://doi.org/10.1007/11505730_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26545-0

  • Online ISBN: 978-3-540-31676-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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