Retinal Vascular Network Topology Reconstruction and Artery/Vein Classification via Dominant Set Clustering
- Submitting institution
-
Edge Hill University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 20801977
- Type
- D - Journal article
- DOI
-
10.1109/TMI.2019.2926492
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- 8754802
- First page
- 341
- Volume
- 39
- Issue
- 2
- ISSN
- 0278-0062
- Open access status
- Compliant
- Month of publication
- July
- 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
-
9
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The proposed method has attracted 16 citations (google scholar) since its publication in 2020 and has been selected at least 4 times for comparative studies. In particular, it was concluded that “In terms of sensitivity and specificity, the most competitive results are achieved with the method proposed by Zhao et al. [20]” in The Visual Computer, https://doi.org/10.1007/s00371-020-01863-z and “the performance of the proposed method is not as good as that of Zhao et al. [21]” in MICCAI 2020, pp 616-625. It has also been further developed in IEEE TMI, 39(2020) 2904-2919 with the definition of a new performance metric.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
