Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/104033
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dc.creatorZhen Ma
dc.creatorJoão Manuel R. S. Tavares
dc.date.accessioned2022-09-07T22:56:54Z-
dc.date.available2022-09-07T22:56:54Z-
dc.date.issued2017-10-30
dc.identifier.issn0957-4174
dc.identifier.othersigarra:190101
dc.identifier.urihttps://hdl.handle.net/10216/104033-
dc.description.abstractFeatures such as shape and color are indispensable to determine whether a skin lesion is a melanoma or not. However, there are no fixed guidelines to define which features are effective and how to combine them for classification. This lack of definition impedes the development of the automatic analyses of dermoscopic images. In this work, a search for effective features was carried out using a support vector machine. Three image databases were used to verify the feasibility and sensitivity of the automatic classification used. The results showed which features had a major influence on the classification performance, and confirmed the need to use various types of features in this process.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectCiências Tecnológicas, Ciências médicas e da saúde
dc.subjectTechnological sciences, Medical and Health sciences
dc.titleEffective Features to Classify Skin Lesions in Dermoscopic images
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.1016/j.eswa.2017.05.003
dc.subject.fosCiências médicas e da saúde
dc.subject.fosMedical and Health sciences
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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