Cloud-Based Automated Clinical Decision Support System for Detection and Diagnosis of Lung Cancer in Chest CT
- Submitting institution
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The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 7391
- Type
- D - Journal article
- DOI
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10.1109/jtehm.2019.2955458
- Title of journal
- IEEE Journal of Translational Engineering in Health and Medicine
- Article number
- 4300113
- First page
- -
- Volume
- 8
- Issue
- -
- ISSN
- 2168-2372
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2019
- 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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8
- Research group(s)
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E - OAK
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes a new solution for automatic analysis of CT scan images for accurate and efficient lung nodule detection. A follow-up project (Clever-dREAMS MRC confidence in concept grant, https://www.sheffield.ac.uk/dcs/research/current-grants) with Sheffield Children Hospital has been funded to apply the image segmentation techniques described in this paper for automatic analysis of Skeletal Dysplasia MRI in children, to create a tool for radiographers locally and nationally. In the future we expect the technology to be used in the clinical setting.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -