Skin lesions characterisation utilising clustering algorithms

Authors:
Sotiris K. Tasoulis;Charalampos N. Doukas;Ilias Maglogiannis;Vassilis P. Plagianakos
Affiliations:
Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece;Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi, Samos, Greece;Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece;Department of Computer Science and Biomedical Informatics, University of Central Greece, Lamia, Greece
Venue:
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
Year:
2010

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Abstract

In this paper we propose a clustering technique for the recognition of pigmented skin lesions in dermatological images It is known that computer vision-based diagnosis systems have been used aiming mostly at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumour The feature extraction is performed utilising digital image processing methods, i.e segmentation, border detection, colour and texture processing The proposed method belongs to a class of clustering algorithms which are very successful in dealing with high dimensional data, utilising information driven by the Principal Component Analysis Experimental results show the high performance of the algorithm against other methods of the same class.