Unsupervised tissue image segmentation through object-oriented texture

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dc.citation.epage2519en_US
dc.citation.spage2516en_US
dc.contributor.authorTosun, Akif Buraken_US
dc.contributor.authorSokmensuer, C.en_US
dc.contributor.authorGündüz-Demir, Çiğdemen_US
dc.coverage.spatialIstanbul, Turkeyen_US
dc.date.accessioned2016-02-08T12:22:48Z
dc.date.available2016-02-08T12:22:48Z
dc.date.issued2010en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 23-26 Aug. 2010en_US
dc.description.abstractThis paper presents a new algorithm for the unsupervised segmentation of tissue images. It relies on using the spatial information of cytological tissue components. As opposed to the previous study, it does not only use this information in defining its homogeneity measures, but it also uses it in its region growing process. This algorithm has been implemented and tested. Its visual and quantitative results are compared with the previous study. The results show that the proposed segmentation algorithm is more robust in giving better accuracies with less number of segmented regions. © 2010 IEEE.en_US
dc.identifier.doi10.1109/ICPR.2010.616en_US
dc.identifier.issn1051-4651
dc.identifier.urihttp://hdl.handle.net/11693/28520
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICPR.2010.616en_US
dc.source.title2010 20th International Conference on Pattern Recognitionen_US
dc.subjectImage segmentationen_US
dc.subjectQuantitative medical image analysisen_US
dc.subjectTexture analysisen_US
dc.subjectMedical image analysisen_US
dc.subjectObject orienteden_US
dc.subjectQuantitative resulten_US
dc.subjectRegion growingen_US
dc.subjectSegmentation algorithmsen_US
dc.subjectSegmented regionsen_US
dc.subjectSpatial informationsen_US
dc.subjectTexture analysisen_US
dc.subjectTissue componentsen_US
dc.subjectTissue image segmentationen_US
dc.subjectTissue imagesen_US
dc.subjectUnsupervised segmentationen_US
dc.subjectAlgorithmsen_US
dc.subjectImage analysisen_US
dc.subjectInformation useen_US
dc.subjectMedical imagingen_US
dc.subjectPattern recognitionen_US
dc.subjectTexturesen_US
dc.subjectTissueen_US
dc.subjectImage segmentationen_US
dc.titleUnsupervised tissue image segmentation through object-oriented textureen_US
dc.typeConference Paperen_US

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