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dc.contributor.authorGharipour, Amin
dc.contributor.authorLiew, Alan Wee-Chung
dc.contributor.editorDimitar P. Filev
dc.date.accessioned2017-05-03T15:20:40Z
dc.date.available2017-05-03T15:20:40Z
dc.date.issued2014
dc.identifier.isbn9781479920723
dc.identifier.issn1544-5615
dc.identifier.refurihttp://www.ieee-wcci2014.org/index.htm
dc.identifier.doi10.1109/FUZZ-IEEE.2014.6891714
dc.identifier.urihttp://hdl.handle.net/10072/67087
dc.description.abstractIn high-throughput applications, accurate segmentation of biomedical images can be considered as an important step for recognizing cells that have the phenotype of interest. In this paper, while conventional fuzzy clustering is not able to implement the local and global spatial information, a novel spatial fuzzy clustering cell image segmentation algorithm is proposed. The segmentation procedure is divided into two stages: the first stage involves processing the local and global spatial information of the given cell image and a final segmentation stage which is based on the idea of conventional fuzzy clustering. Our idea can be considered as a sequential integration of region based methods and fuzzy clustering for cell image segmentation. Experimental results show that the proposed model yields significantly better performance in comparison with several existing methods
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent227493 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherIEEE
dc.publisher.placeUnited States
dc.publisher.urihttp://www.ieee-wcci2014.org/index.htm
dc.relation.ispartofstudentpublicationY
dc.relation.ispartofconferencenameIEEE International Conference on Fuzzy Systems
dc.relation.ispartofconferencetitle2014 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)
dc.relation.ispartofdatefrom2014-07-06
dc.relation.ispartofdateto2014-07-11
dc.relation.ispartoflocationBeijing, PEOPLES R CHINA
dc.relation.ispartofpagefrom216
dc.relation.ispartofpagefrom7 pages
dc.relation.ispartofpageto222
dc.relation.ispartofpageto7 pages
dc.rights.retentionY
dc.subject.fieldofresearchComputer vision
dc.subject.fieldofresearchcode460304
dc.titleFuzzy Clustering Using Local and Global Region Information for Cell Image Segmentation
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
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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