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Adaptive-size dictionary learning using information theoretic criteria for image reconstruction from undersampled k-space data in low field magnetic resonance imaging

Crossref DOI link: https://doi.org/10.1186/s12880-020-00474-3

Published Online: 2020-06-29

Published Print: 2020-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Ahishakiye, Emmanuel https://orcid.org/0000-0001-6598-2111
Van Gijzen, Martin Bastiaan

Tumwiine, Julius

Obungoloch, Johnes
Funding

Funding for this research was provided by:

NWO-WOTRO (W 07.303.101)
License Information

Text and Data Mining valid from 2020-06-29

Version of Record valid from 2020-06-29
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Article History

Received: 5 February 2020

Accepted: 19 June 2020

First Online: 29 June 2020

Ethics approval and consent to participate

: We did not require any administrative permissions to access raw data from LUMC. This is a joint project between LUMC, MUST, TU Delft and PSU. We freely exchange data, codes and methodologies.

: Not applicable.

: The authors declare that they have no competing interests.

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