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dc.creatorMaglogiannis, I.en
dc.creatorDoukas, C. N.en
dc.date.accessioned2015-11-23T10:38:21Z
dc.date.available2015-11-23T10:38:21Z
dc.date.issued2009
dc.identifier10.1109/titb.2009.2017529
dc.identifier.issn1089-7771
dc.identifier.urihttp://hdl.handle.net/11615/30490
dc.description.abstractDuring the last years, computer-vision-based diagnosis systems have been used in several hospitals and dermatology clinics, aiming mostly at the early detection of skin cancer, and more specifically, the recognition of malignant melanoma tumour. In this paper, we review the state of the art in such systems by first presenting the installation, the visual features used for skin lesion classification, and the methods for defining them. Then, we describe how to extract these features through digital image processing methods, i.e., segmentation, border detection, and color and texture processing, and we present the most prominent techniques for skin lesion classification. The paper reports the statistics and the results of the most important implementations that exist in the literature, while it compares the performance of several classifiers on the specific skin lesion diagnostic problem and discusses the corresponding findings.en
dc.source.uri<Go to ISI>://WOS:000269518900007
dc.subjectClassification methodsen
dc.subjectcomputer visionen
dc.subjectdermoscopyen
dc.subjectmelanomaen
dc.subjectpatternen
dc.subjectanalysisen
dc.subjectskin canceren
dc.subjectMALIGNANT-MELANOMAen
dc.subjectIMAGE-ANALYSISen
dc.subjectDIGITAL DERMOSCOPYen
dc.subject7-POINTen
dc.subjectCHECKLISTen
dc.subjectEARLY-DIAGNOSISen
dc.subjectNEURAL-NETWORKen
dc.subjectCOLOR IMAGESen
dc.subjectCLASSIFICATIONen
dc.subjectIDENTIFICATIONen
dc.subjectDERMATOSCOPYen
dc.subjectComputer Science, Information Systemsen
dc.subjectComputer Science,en
dc.subjectInterdisciplinary Applicationsen
dc.subjectMathematical & Computational Biologyen
dc.subjectMedical Informaticsen
dc.titleOverview of Advanced Computer Vision Systems for Skin Lesions Characterizationen
dc.typejournalArticleen


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