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dc.contributor.authorLam, Bensonen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.authorLiew, Alan Wee-Chungen_US
dc.contributor.editorHao Shi, Yanchun Zhang, Murk J. Bottema, Brian C. Lovell, Anthony J. Maederen_US
dc.date.accessioned2017-04-24T12:52:04Z
dc.date.available2017-04-24T12:52:04Z
dc.date.issued2009en_US
dc.date.modified2010-06-03T09:25:57Z
dc.identifier.refurihttp://dicta2009.vu.edu.au/en_AU
dc.identifier.doi10.1109/DICTA.2009.14en_AU
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.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent959710 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEE Conference Publishing Servicesen_US
dc.publisher.placeAustraliaen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencenameDigital Image Computing: Techniques and Applications, DICTA2009en_US
dc.relation.ispartofconferencetitleProceedings 2009 Digital Image Computing: Techniques and Applications DICTA 2009en_US
dc.relation.ispartofdatefrom2009-12-01en_US
dc.relation.ispartofdateto2009-12-03en_US
dc.relation.ispartoflocationMelbourne, Australiaen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchImage Processingen_US
dc.subject.fieldofresearchcode080106en_US
dc.titleOptimizing Sharpness Measure for Bright Lesion Detection in Retinal Image Analysisen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright 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.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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

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