Automatic 2D/3D Vessel Enhancement in Multiple Modality Images Using a Weighted Symmetry Filter
- Submitting institution
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Edge Hill University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 20350805
- Type
- D - Journal article
- DOI
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10.1109/TMI.2017.2756073
- Title of journal
- IEEE Transactions on Medical Imaging
- Article number
- 8049478
- First page
- 438
- Volume
- 37
- Issue
- 2
- ISSN
- 0278-0062
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2018
- 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
-
8
- Research group(s)
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-
- Citation count
- 32
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The proposed WSF method has attracted 56 citations (google scholar) since its publication in 2018 and has been selected more than 9 times for comparative studies, including IEEE Journal of Biomedical and Health Informatics 24(12)(2020) 3397-3407; Applied Optics 57(25)(2018) 7287-7295; and in particular Neurocomputing 380(2020) 162-179 that concluded “our method and WSF have a good enhancement effect both on large-sized and small-sized vascularity”. It was adopted for pre-processing in EMBC, 2020: 1360-1363 and further developed at least two times for applications and performance improvement in Structural Health Monitoring 19(5)(2020) 1590-1601 and in ACVIS 2020: 251-261 respectively.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -