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dc.contributor.authorSoares, J.V.B.
dc.contributor.authorLeandro, J.J.G.
dc.contributor.authorCesar, R.M., Jr.
dc.contributor.authorJelinek, H.F.
dc.contributor.authorCree, Michael J.
dc.coverage.spatialUnited Statesen_NZ
dc.date.accessioned2008-11-23T22:26:22Z
dc.date.available2008-11-23T22:26:22Z
dc.date.issued2006-09
dc.identifier.citationSoares, J. V. B., Leandro, J. J. G., Cesar, R. M., Jr., Jelinek, H. F. & Cree, M, J. (2006). Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Transactions on Medical Imaging, 25(9), 1214- 1222.en_US
dc.identifier.issn0278-0062
dc.identifier.urihttps://hdl.handle.net/10289/1452
dc.description.abstractWe present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al.,2004) and STARE (Hoover et al.,2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver operating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for researchers interested in implementation details, evaluation, or development of methods.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherI E E Een_NZ
dc.rightsCopyright 2006 IEEE Transactions on Medical Imaging. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the IEEE Transactions on Medical Imaging.en_US
dc.titleRetinal vessel segmentation using the 2-D Gabor wavelet and supervised classificationen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1109/TMI.2006.879967en_US
dc.relation.isPartOfIEEE Transactions on Medical Imagingen_NZ
pubs.begin-page1214en_NZ
pubs.elements-id32029
pubs.end-page1222en_NZ
pubs.issue9en_NZ
pubs.volume25en_NZ
uow.identifier.article-no9en_NZ


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