Automated detection of proliferative diabetic retinopathy using a modified line operator and dual classification
- Submitting institution
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Kingston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11-16-1350
- Type
- D - Journal article
- DOI
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10.1016/j.cmpb.2014.02.010
- Title of journal
- Computer Methods and Programs in Biomedicine
- Article number
- -
- First page
- 247
- Volume
- 114
- Issue
- -
- ISSN
- 0169-2607
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- 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
-
-
- Research group(s)
-
-
- Citation count
- 52
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The methodology described in this paper offers a technique that has enabled progress to be made in the challenging task relating to the detection of new vessels in retinal fundus images. As far as we are aware, the approach of dual classification had not been applied to new vessel analysis previously. Novel techniques have only recently emerged that are capable of detecting faint, and difficult to see, new vessels within retinal images.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -