Comparison of HOG, MSER, SIFT, FAST, LBP and CANNY features for cell detection in histopathological images

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dc.contributor.authorOzturk, Saban
dc.contributor.authorAkdemir, Bayram
dc.date.accessioned2020-03-26T19:53:10Z
dc.date.available2020-03-26T19:53:10Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractCell segmentation and counting has a very important role in diagnosing diseases and in the treatment process. But the complexity of the histopathological images and the differences in cell groups make this process very difficult, even for an expert. In order to facilitate this process, analysis of histopathological images is performed by using computer vision methods. This paper presents the use of different feature extraction methods for cell detection in histopathological images and the comparison of the results of these algorithms. For this reason, HOG, MSER, SIFT, FAST, LBP and CANNY feature extraction algorithms are used. The aim of the study is to determine cells using different feature extraction methods and to determine which of these feature extraction algorithms will be more successful. Firstly, image pre-processing has been applied to clear the noises in the histopathological images. Then, feature extraction algorithms are applied to image, respectively. Finally, the successes of different feature extraction algorithms have been compared.en_US
dc.identifier.doi10.29042/2018-3321-3325en_US
dc.identifier.endpage3325en_US
dc.identifier.issn2277-3495en_US
dc.identifier.issn2319-5592en_US
dc.identifier.issue3en_US
dc.identifier.pmid#YOKen_US
dc.identifier.startpage3321en_US
dc.identifier.urihttps://dx.doi.org/10.29042/2018-3321-3325
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36427
dc.identifier.volume8en_US
dc.identifier.wosWOS:000433225200002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherBIOAXIS DNA RESEARCH CENTRE PRIVATE LIMITEDen_US
dc.relation.ispartofHELIXen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectHOGen_US
dc.subjectMSERen_US
dc.subjectSIFTen_US
dc.subjectFASTen_US
dc.subjectLBPen_US
dc.subjectcannyen_US
dc.subjecthistopathological imageen_US
dc.subjectcell countingen_US
dc.titleComparison of HOG, MSER, SIFT, FAST, LBP and CANNY features for cell detection in histopathological imagesen_US
dc.typeArticleen_US

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