Dictionary learning and time sparsity for dynamic MR data reconstruction
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2170
- Type
- D - Journal article
- DOI
-
10.1109/TMI.2014.2301271
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- -
- First page
- 979
- Volume
- 33
- Issue
- 4
- ISSN
- 1558-254X
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
10.1109/TMI.2014.2301271
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 111
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper introduces one of the first machine learning algorithms for the reconstruction of dynamic MR images from highly under-sampled data. The results directly underpin a subsequent EPSRC programme grant (SmartHeart; EP/P001009/1; £5.1M; PI: Rueckert), which builds upon and further develops the research direction pioneered in this paper (http://wp.doc.ic.ac.uk/smartheart). Based on this work, Caballero (PhD student under Rueckert’s supervision) joined the start-up Magic Pony to develop similar techniques for super-resolution video imaging. The paper led to several invitations to conference keynotes, including WBIR 2014, GTC 2017 and MIUA 2017.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
