The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Measurement of Retinal Vessel Widths From Fundus Images Based on 2-D Modeling
Open accessAbstract
Changes in retinal vessel diameter are an important sign of diseases such as hypertension, arteriosclerosis and diabetes mellitus. Obtaining precise measurements of vascular widths is a critical and demanding process in automated retinal image analysis as the typical vessel is only a few pixels wide. This paper presents an algorithm to measure the vessel diameter to subpixel accuracy. The diameter measurement is based on a two-dimensional difference of Gaussian model, which is optimized to fit a two-dimensional intensity vessel segment. The performance of the method is evaluated against Brinchmann-Hansen's half height, Gregson's rectangular profile and Zhou's Gaussian model. Results from 100 sample profiles show that the presented algorithm is over 30% more precise than the compared techniques and is accurate to a third of a pixel.
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Cites
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Cited by
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification
Soares, J. V. B., Leandro, J. J. G., Cesar, R. M., Jelinek, H. F., & Cree, M. J. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.879967 · Cited by 1,497
Marín, D., Aquino, A., Gegundez-Arias, M. E., & Bravo, J. M. (2011) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2064333 · Cited by 929
Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification
Ricci, E., & Perfetti, R. (2007) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.898551 · Cited by 818
An Active Contour Model for Segmenting and Measuring Retinal Vessels
Al-Diri, B., Hunter, A., & Steel, D. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2009.2017941 · Cited by 431
Self-citationAn approach to localize the retinal blood vessels using bit planes and centerline detection
Fraz, M. M., Barman, S. A., Remagnino, P., Hoppe, A., Basit, A., Uyyanonvara, B., Rudnicka, A. R., & Owen, C. G. (2012) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2011.08.009 · Cited by 340
Metadata
- Authors
- Lowell, J., Hunter, A., Steel, D., Basu, A., Ryder, R., & Kennedy, R. L.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2004-10
- Volume
- 23
- Issue
- 10
- Pages
- 1196-1204
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2155122478
- Cited by
- 255
- References
- 22
- FWCI
- 7.49
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
