Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data
- Submitting institution
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University College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13964
- Type
- D - Journal article
- DOI
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10.1016/j.neuroimage.2014.10.026
- Title of journal
- Neuroimage
- Article number
- -
- First page
- 32
- Volume
- 105
- Issue
- -
- ISSN
- 1053-8119
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Citation count
- 139
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- AMICO is a novel model-fitting algorithm for estimating tissue microstructure from MRI data. It delivers 1,000-fold acceleration over the standard nonlinear least-squares, reducing typical image-reconstruction time from days to merely minutes, without compromising integrity. Its impact is transformative, making various advanced microstructure imaging techniques accessible both in clinical routines and for large-scale imaging studies. Most notably, AMICO enabled the deployment of today’s most popular microstructure imaging technique (NODDI) as part of the landmark UK Biobank imaging study, involving 100,000 subjects, the largest of its kind in the world. Without AMICO, this would not have been possible.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -