Intensity and Compactness Enabled Saliency Estimation for Leakage Detection in Diabetic and Malarial Retinopathy
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 21867052
- Type
- D - Journal article
- DOI
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10.1109/TMI.2016.2593725
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- 7518662
- First page
- 51
- Volume
- 36
- Issue
- 1
- ISSN
- 0278-0062
- Open access status
- Not compliant
- Month of publication
- July
- Year of publication
- 2016
- URL
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- Supplementary information
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- Request cross-referral to
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- 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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6
- Research group(s)
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-
- Citation count
- 24
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Presents a novel approach for automatic leakage detection from fundus images, through saliency detection and analysis in intensity and compactness. Work done by a British-Sino multi-partnership project, reported in IEEE TMI (leading journal for medical image modelling and analysis). Work has led to cost-effective applications of computer aided diagnostic systems, including those for glaucoma diagnosis (Haleem et al, 2018), melanoma skin lesion segmentation (Olugbara et al, 2018), and retinal vascular network reconstruction (Zhao et al, 2019).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -