title: An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images.
abstract: Segmentation is an important step in computer-aided diagnostic systems for pigmented skin lesions, since that a good definition of the lesion area and its boundary at the image is very important to distinguish benign from malignant cases. In this paper a new skin lesion segmentation method is proposed. This method uses Independent Component Analysis to locate skin lesions in the image, and this location information is further refined by a Level-set segmentation method. Our method was evaluated in 141 images and achieved an average segmentation error of 16.55%, lower than the results for comparable state-of-the-art methods proposed in literature.
authors.affiliation: Instituto de Informática, Universidade Federal do Rio Grande do Sul Avenida Bento Goncalves, RS 91501-970, Brazil. fpgcavalcanti@inf.ufrgs.br
authors.forename: Pablo G
authors.initials: PG
authors.lastname: Cavalcanti
authors.forename: Jacob
authors.initials: J
authors.lastname: Scharcanski
authors.forename: Leandro E
authors.initials: LE
authors.lastname: Di Persia
authors.forename: Diego H
authors.initials: DH
authors.lastname: Milone
mesh_terms: D000465:Algorithms; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008545:Melanoma / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010859:Pigmentation Disorders / Q000473:pathology*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000473:pathology*