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Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate

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Computational Diffusion MRI

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

Recently, super-resolution methods for diffusion MRI capable of retrieving high-resolution diffusion-weighted images were proposed, yielding a resolution beyond the scanner hardware limitations. These techniques rely on acquiring either one isotropic or several anisotropic low-resolution versions of each diffusion-weighted image. In the present work, a variational formulation of joint super-resolution of all diffusion-weighted images is presented which takes advantage of interrelations between similar diffusion-weighted images. These interrelations allow to use only one anisotropic low-resolution version of each diffusion-weighted image and to retrieve its missing high-frequency components from other images which have a similar q-space coordinate but a different resolution-anisotropy orientation. An acquisition scheme that entails complementary resolution-anisotropy among neighboring q-space points is introduced. High-resolution images are recovered at reduced scan time requirements compared to state-of-the-art anisotropic super-resolution methods. The introduced principles of joint super-resolution thus have the potential to further improve the performance of super-resolution methods.

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Acknowledgements

Grant support: Deutsche Telekom Foundation.

Author information

Authors and Affiliations

  1. GE Global Research, Garching, Germany

    Vladimir Golkov, Jonathan I. Sperl, Marion I. Menzel & Tim Sprenger

  2. Technische Universität München, Garching, Germany

    Vladimir Golkov, Tim Sprenger, Axel Haase & Daniel Cremers

  3. GE Global Research, Niskayuna, NY, USA

    Ek Tsoon Tan, Luca Marinelli & Christopher J. Hardy

Authors
  1. Vladimir Golkov
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  2. Jonathan I. Sperl
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  3. Marion I. Menzel
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  4. Tim Sprenger
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  5. Ek Tsoon Tan
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  6. Luca Marinelli
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  7. Christopher J. Hardy
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  8. Axel Haase
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  9. Daniel Cremers
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Corresponding author

Correspondence to Vladimir Golkov .

Editor information

Editors and Affiliations

  1. Harvard Medical School Brigham and Women's Hospital, Boston, Massachusetts, USA

    Lauren O'Donnell

  2. Dept. of Computer Science, University College London Dept of Computer Science, London, United Kingdom

    Gemma Nedjati-Gilani

  3. Harvard Medical School Brigham and Women's Hospital, Boston, Massachusetts, USA

    Yogesh Rathi

  4. University Medical Center Freiburg Department of Radiology, Freiburg, Germany

    Marco Reisert

  5. Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, Queen Square House, Queen Square, London, United Kingdom

    Torben Schneider

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© 2014 Springer International Publishing Switzerland

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Golkov, V. et al. (2014). Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate. In: O'Donnell, L., Nedjati-Gilani, G., Rathi, Y., Reisert, M., Schneider, T. (eds) Computational Diffusion MRI. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-11182-7_16

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