Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/13929
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dc.contributor.authorEltayef, K-
dc.contributor.authorli, Y-
dc.contributor.authorliu, X-
dc.coverage.spatialDubai, UAE-
dc.date.accessioned2017-01-25T14:14:57Z-
dc.date.available2017-01-25T14:14:57Z-
dc.date.issued2016-
dc.identifier.citation2016 International Conference on Communication, Image and Signal Processing (CCISP 2016), 18-20 November, Dubai, (2016)en_US
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/13929-
dc.description.abstractMalignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noise from images, preprocessing step is carried out by applying a bank of directional lters. and therefore, Image inpainting method is implemented to ll in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced compared to alternative methods.en_US
dc.language.isoenen_US
dc.publisherAisa Pacific Institute of Science and Engineeringen_US
dc.sourceInternational Conference on Communication, Image and Signal Processing-
dc.sourceInternational Conference on Communication, Image and Signal Processing-
dc.subjectDermoscopy imageen_US
dc.subjectMelanomaen_US
dc.subjectLesion detectionen_US
dc.titleDetection of melanoma skin cancer in dermoscopy imagesen_US
dc.typeConference Paperen_US
pubs.publication-statusPublished-
Appears in Collections:Dept of Computer Science Research Papers

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