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dc.contributor.authorCornforth, D.J.
dc.contributor.authorJelinek, Herbert J.
dc.contributor.authorLeandro, J.J.G.
dc.contributor.authorSoares, J.V.B.
dc.contributor.authorCesar, R.M., Jr.
dc.contributor.authorCree, Michael J.
dc.contributor.authorMitchell, P.
dc.contributor.authorBossomaier, T.
dc.coverage.spatialConference held at Cairns, Australiaen_NZ
dc.date.accessioned2009-10-22T01:36:12Z
dc.date.available2009-10-22T01:36:12Z
dc.date.issued2005
dc.identifier.citationCornforth, D. J., Jelinek, H. F., Leandro, J. G., Soares, J. V., Cesar, R. M., Cree, M. J., Mitchell, P. & Bossomaier, T.(2005). Development of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathy. Complexity International, 11, 50-61.en
dc.identifier.urihttps://hdl.handle.net/10289/3298
dc.description.abstractAutomated image processing has the potential to assist in the early detection of diabetes, by detecting changes in blood vessel diameter and patterns in the retina. This paper describes the development of segmentation methodology in the processing of retinal blood vessel images obtained using non-mydriatic colour photography. The methods used include wavelet analysis, supervised classifier probabilities and adaptive threshold procedures, as well as morphology-based techniques. We show highly accurate identification of blood vessels for the purpose of studying changes in the vessel network that can be utilized for detecting blood vessel diameter changes associated with the pathophysiology of diabetes. In conjunction with suitable feature extraction and automated classification methods, our segmentation method could form the basis of a quick and accurate test for diabetic retinopathy, which would have huge benefits in terms of improved access to screening people for risk or presence of diabetes.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.relation.urihttp://www.complexity.org.au/ci/vol11/cornfo02/en
dc.rightsThis article has been published in the journal: Complexity International. ©2005 Complexity International. Used with permission.en
dc.sourceThe 8th Asia Pacific Symposium on Intelligent and Evolutionary Systemsen_NZ
dc.subjectengineeringen
dc.titleDevelopment of retinal blood vessel segmentation methodology using wavelet transforms for assessment of diabetic retinopathyen
dc.typeJournal Articleen
dc.relation.isPartOfComplexity Internationalen_NZ
pubs.begin-page50en_NZ
pubs.elements-id15415
pubs.end-page61en_NZ
pubs.finish-date2004-12-07en_NZ
pubs.start-date2004-12-06en_NZ
pubs.volume11en_NZ


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