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dc.contributor.authorTan Xiao, Jian
dc.contributor.authorNazahah, Mustafa
dc.contributor.authorMohd Yusoff, Mashor
dc.contributor.authorKhairul Shakir, Ab Rahman
dc.date.accessioned2020-12-16T08:27:31Z
dc.date.available2020-12-16T08:27:31Z
dc.date.issued2019
dc.identifier.citationJournal of Physics: Conference Series, vol.1372, 2019, 6 pagesen_US
dc.identifier.issn1742-6588 (print)
dc.identifier.issn1742-6596 (online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/69025
dc.descriptionLink to publisher's homepage at https://iopscience.iop.org/en_US
dc.description.abstractThis study proposes a modified initialization approach for the conventional FCM, namely FCM with guided initialization. The FCM with guided initialization was implemented to segment the relevant regions in the breast histopathology images. The initialization method to select initial centers is based on the Cyan (C) channel histogram. Area Overlap Measure (AOM) and Combined Equal Importance (CEI) were used to evaluate the performance of the proposed FCM with guided initialization. The obtained AOM and CEI for the overall dataset achieved promising results: 0.89 in AOM and 0.88 in CEI. When comparing the number of iterations required to complete the proposed FCM clustering algorithm, the FCM with guided initialization is found to be effective in reducing the search space by showing a lower number of iterations.en_US
dc.language.isoenen_US
dc.publisherIOP Publishingen_US
dc.relation.ispartofseriesInternational Conference on Biomedical Engineering (ICoBE);
dc.subjectRelevant regionen_US
dc.subjectFCMen_US
dc.subjectBreast histopathologyen_US
dc.titleSegmentation of Relevant Region in Breast Histopathology Images using FCM with Guided Initializationen_US
dc.typeArticleen_US
dc.identifier.urlhttps://iopscience.iop.org/article/10.1088/1742-6596/1372/1/012028/pdf
dc.contributor.urlnazahah@unimap.edu.myen_US


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