title: Comparison of segmentation methods for automatic diagnosis of dermoscopy images.
abstract: Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The effective implementation of such a tool could lead to a reduction in the number of cases selected for exeresis, with obvious benefits both to the patients and to the health care system. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) image segmentation, (ii) feature extraction and feature selection, (iii) lesion classification. This paper presents a comparison of segmentation methods applied to 50 dermoscopic image analysis, along with a clinical evaluation of each segmentation result performed by an experienced dermatologist.
authors.affiliation: Faculdade de Ciências da Universidade do Porto, Departamento de Matemática Aplicada, Porto, Portugal. tmendo@fc.up.pt
authors.forename: Teresa
authors.initials: T
authors.lastname: Mendonca
authors.forename: Andre R S
authors.initials: AR
authors.lastname: Marcal
authors.forename: Angela
authors.initials: A
authors.lastname: Vieira
authors.forename: Jacinto C
authors.initials: JC
authors.lastname: Nascimento
authors.forename: Margarida
authors.initials: M
authors.lastname: Silveira
authors.forename: Jorge S
authors.initials: JS
authors.lastname: Marques
authors.forename: Jorge
authors.initials: J
authors.lastname: Rozeira
mesh_terms: D000465:Algorithms; D046169:Dermoscopy; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D012871:Skin Diseases / Q000175:diagnosis