Bootstrap-Optimised Regularised Image Reconstruction for Emission Tomography
- Submitting institution
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King's College London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 128352874
- Type
- D - Journal article
- DOI
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10.1109/TMI.2019.2956878
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- 8959175
- First page
- 2163
- Volume
- 39
- Issue
- 6
- ISSN
- 0278-0062
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2020
- URL
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- Supplementary information
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- 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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1
- Research group(s)
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- PET is used for imaging diseases of the brain, heart and body, but it is seriously affected by noise in the images. It is therefore always necessary to mitigate for noise, but there has been a lack of objective methodology for choosing the right level of noise mitigation. This paper proposes an original solution to this decades-old problem. The method is automatic and robust, delivering precisely-optimised image quality for each PET scan, without user intervention. The method has drawn much interest, is currently being patented (UK Patent Application No. PCT/GB2020/050876), with industry and venture capitalists interested in its clinical potential.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -