title: Classification of dermatological images using advanced clustering techniques.
abstract: Computer vision-based diagnosis systems have been widely used in dermatology, aiming at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. This paper proposes a novel clustering technique for the characterization and categorization of pigmented skin lesions in dermatological images. Appropriate image processing techniques (i.e. segmentation, border detection, color and texture processing) are utilized for feature extraction. The proposed method uses Principal Component Analysis and is considered appropriate, since it is suitable for problems with high dimensional data. Initial experimental results have proved the superiority of this method against traditional ones.
authors.affiliation: Department of Computer Science and Biomedical Informatics, University of Central Greece, Papassiopoulou 2-4, Lamia, 35100, Greece. stas@ucg.gr
authors.forename: S K
authors.initials: SK
authors.lastname: Tasoulis
authors.forename: C N
authors.initials: CN
authors.lastname: Doukas
authors.forename: I
authors.initials: I
authors.lastname: Maglogiannis
authors.forename: V P
authors.initials: VP
authors.lastname: Plagianakos
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008545:Melanoma / Q000175:diagnosis*; D012878:Skin Neoplasms / Q000175:diagnosis