Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/13929
Title: Detection of melanoma skin cancer in dermoscopy images
Authors: Eltayef, K
li, Y
liu, X
Keywords: Dermoscopy image;Melanoma;Lesion detection
Issue Date: 2016
Publisher: Aisa Pacific Institute of Science and Engineering
Citation: 2016 International Conference on Communication, Image and Signal Processing (CCISP 2016), 18-20 November, Dubai, (2016)
Abstract: Malignant 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.
URI: http://bura.brunel.ac.uk/handle/2438/13929
Appears in Collections:Dept of Computer Science Research Papers

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