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

Golkov V, Sperl JI, Menzel MI, Sprenger T, Tan ET, Marinelli L, Hardy CJ, Haase A, Cremers D (2014)

Publication Type: Conference contribution

Publication year: 2014

Publisher: springer berlin

Book Volume: 39

Pages Range: 181-191

Conference Proceedings Title: Mathematics and Visualization

Event location: Boston, MA, USA

ISBN: 9783319111810

DOI: 10.1007/978-3-319-11182-7_16

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 diffusionweighted image. In the present work, a variational formulation of joint superresolution 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 superresolution methods. The introduced principles of joint super-resolution thus have the potential to further improve the performance of super-resolution methods.

Involved external institutions

GE Deutschland Holding GmbH DE Germany (DE) GE Global Research US United States (USA) (US) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Golkov, V., Sperl, J.I., Menzel, M.I., Sprenger, T., Tan, E.T., Marinelli, L.,... Cremers, D. (2014). Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate. In Torben Schneider, Marco Reisert, Lauren O’Donnell, Yogesh Rathi, Gemma Nedjati-Gilani (Eds.), Mathematics and Visualization (pp. 181-191). Boston, MA, USA: springer berlin.

MLA:

Golkov, Vladimir, et al. "Joint Super-Resolution Using Only One Anisotropic Low-Resolution Image per q-Space Coordinate." Proceedings of the MICCAI Workshop on Computational Diffusion MRI, CDMRI 2014 held under the auspices of the 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, Boston, MA, USA Ed. Torben Schneider, Marco Reisert, Lauren O’Donnell, Yogesh Rathi, Gemma Nedjati-Gilani, springer berlin, 2014. 181-191.

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