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Segmentation of brain MRI images by using type-II fuzzy clustering algorithm

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dc.contributor.authorToker, Ipek
dc.contributor.authorDogan, Berat
dc.contributor.authorPinar, Sedef Kent
dc.contributor.ituauthorKent, Pınar Sedef
dc.date.accessioned2026-01-25T05:17:21Z
dc.date.issued2015-05-01
dc.description.abstractIn this study, segmentation of Multiple Sclerosis (MS) lesions from synthetic brain MRI images was aimed by using fuzzy clustering algorithms. The performances of fuzzy c-means algorithm and type-2 fuzzy c-means algorithm were compared. After several experiments it was shown that, the type-2 fuzzy c-means algorithm performed better than the standard fuzzy c-means algorithm.
dc.description.urihttps://doi.org/10.1109/siu.2015.7130233
dc.description.urihttps://doi.org/10.1109/SIU.2015.7130233
dc.description.urihttps://dx.doi.org/10.1109/siu.2015.7130233
dc.identifier.doi10.1109/siu.2015.7130233
dc.identifier.endpage1912
dc.identifier.openairedoi_dedup___::6b7fd0caf3a375d566370184e701e654
dc.identifier.orcid0000-0003-4810-1970
dc.identifier.orcid0000-0002-8396-2920
dc.identifier.startpage1909
dc.identifier.urihttps://hdl.handle.net/11527/46813
dc.publisherIEEE
dc.relation.ispartof2015 23nd Signal Processing and Communications Applications Conference (SIU)
dc.titleSegmentation of brain MRI images by using type-II fuzzy clustering algorithm
dc.typeArticle
dspace.entity.typePublication
person.identifier.orcid0000-0002-8396-2920

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