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Two segmentation methods for the diagnosis of malignant melanoma

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dc.contributor.authorPark, S.-
dc.contributor.authorLee, H.-
dc.contributor.authorKwon, K.-
dc.date.accessioned2023-04-27T19:40:52Z-
dc.date.available2023-04-27T19:40:52Z-
dc.date.issued2021-
dc.identifier.issn1927-5307-
dc.identifier.issn1927-5307-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/5578-
dc.description.abstractAutomatic diagnosis of malignant melanoma highly depends on the segmentation methods used for the suspicious lesion. We suggest the parameter selection method (PSM) and maximum area method (MAM) for the segmentation of the lesion to be diagnosed. Herein, these segmentation methods are compared to a skin cancer expert’s segmentation and three other conventional algorithms. The diagnoses of malignant melanoma based on the two suggested, three conventional, and expert’s segmentation are compared with respect to sensitivity, specificity, and accuracy. © 2021 the author(s).-
dc.format.extent16-
dc.language영어-
dc.language.isoENG-
dc.publisherSCIK Publishing Corporation-
dc.titleTwo segmentation methods for the diagnosis of malignant melanoma-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.28919/JMCS/5650-
dc.identifier.scopusid2-s2.0-85106862122-
dc.identifier.bibliographicCitationJournal of Mathematical and Computational Science, v.11, no.3, pp 3361 - 3376-
dc.citation.titleJournal of Mathematical and Computational Science-
dc.citation.volume11-
dc.citation.number3-
dc.citation.startPage3361-
dc.citation.endPage3376-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.subject.keywordAuthorABCD criteria-
dc.subject.keywordAuthorImage segmentation-
dc.subject.keywordAuthorMaliganant melanoma-
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