Attenuation Correction Synthesis for Hybrid PET-MR Scanners: Application to Brain Studies
- Submitting institution
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University College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13934
- Type
- D - Journal article
- DOI
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10.1109/TMI.2014.2340135
- Title of journal
- IEEE TRANSACTIONS ON MEDICAL IMAGING
- Article number
- 12
- First page
- 2332
- Volume
- 33
- Issue
- 12
- ISSN
- 0278-0062
- Open access status
- Out of scope for open access requirements
- Month of publication
- December
- 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
-
14
- Research group(s)
-
-
- Citation count
- 165
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Solves a pressing problem in quantification of PET by generating synthetic CT images through a novel multi-atlas information propagation scheme for the first time, matching the MRI-derived patient’s morphology to a database of MRI/CT pairs. Enabled patient-specific attenuation correction, (not directly available in hybrid PET/MR scanners). Results showed significant improvements in CT synthesis and PET reconstruction accuracy compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method. Led to sponsorship of two studentships from Siemens on MRAC in lungs. opened an active research domain in synthetic CT generation including extension to machine learning techniques.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -