An Image Reconstruction Algorithm for Electrical Impedance Tomography Using Adaptive Group Sparsity Constraint
- Submitting institution
-
University of Edinburgh
(joint submission with Heriot-Watt University)
- Unit of assessment
- 12 - Engineering
- Output identifier
- 58759802
- Type
- D - Journal article
- DOI
-
10.1109/TIM.2017.2701098
- Title of journal
- IEEE Transactions on Instrumentation and Measurement
- Article number
- -
- First page
- 2295
- Volume
- 66
- Issue
- 9
- ISSN
- 0018-9456
- Open access status
- Compliant
- Month of publication
- May
- Year of publication
- 2017
- 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
-
1
- Research group(s)
-
C - SSS
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work reports a new image reconstruction approach for electrical impedance tomography that outperforms previous methods in terms of image quality and computational cost. The outcomes of the work were the foundation of an EPSRC funded project “Cerebral Blood Flow Imaging based on 3D Electrical Impedance Tomography” (EP/P006833/1, £100,894; ranked first in category). The work has been influential in a wide range of tomography techniques, such as computed-tomography (CT) (DOI: 10.1002/cnm.3101), and electromagnetic tomography (EMT) (DOI: 10.1109/JSEN.2018.2809485).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
