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dc.contributor.authorLam, Benson SY
dc.contributor.authorGao, Yongsheng
dc.contributor.authorLiew, Alan Wee-Chung
dc.contributor.editorShi, H
dc.contributor.editorZhang, YC
dc.contributor.editorBottema, MJ
dc.contributor.editorLovell, BC
dc.contributor.editorMaeder, AJ
dc.date.accessioned2017-05-03T15:20:03Z
dc.date.available2017-05-03T15:20:03Z
dc.date.issued2009
dc.date.modified2010-06-03T09:25:57Z
dc.identifier.isbn978-1-4244-5297-2
dc.identifier.refurihttp://dicta2009.vu.edu.au/
dc.identifier.doi10.1109/DICTA.2009.14
dc.identifier.urihttp://hdl.handle.net/10072/30006
dc.description.abstractDue to the spherical shape nature of retina and the illumination effect, detecting bright lesions in a retinal image is a challenging problem. Existing methods depend heavily on a prior knowledge about lesions, which either a user-defined parameter is employed or a supervised learning technique is adopted to estimate the parameter. In this paper, a novel sharpness measure is proposed, which indicates the degree of sharpness of bright lesions in the whole retinal image. It has a sudden jump at the optimal parameter. A polynomial fitting technique is used to capture this jump. We have tested our method on a public available dataset. Experimental results show that the proposed unsupervised approach is able to detect bright lesions accurately in an unhealthy retinal image and it outperforms existing supervised learning method. Also, the proposed method reports no abnormality for a healthy retinal image.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent959710 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE Conference Publishing Services
dc.publisher.placeAustralia
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencename11th Conference on Digital Image Computing: Techniques and Applications
dc.relation.ispartofconferencetitle2009 DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA 2009)
dc.relation.ispartofdatefrom2009-12-01
dc.relation.ispartofdateto2009-12-03
dc.relation.ispartoflocationMelbourne, AUSTRALIA
dc.relation.ispartofpagefrom19
dc.relation.ispartofpagefrom2 pages
dc.relation.ispartofpageto+
dc.relation.ispartofpageto2 pages
dc.rights.retentionY
dc.subject.fieldofresearchImage processing
dc.subject.fieldofresearchcode460306
dc.titleOptimizing Sharpness Measure for Bright Lesion Detection in Retinal Image Analysis
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
gro.date.issued2009
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorLiew, Alan Wee-Chung


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    Contains papers delivered by Griffith authors at national and international conferences.

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