Separability Analysis of Color Classes on Dermoscopic Images

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2012

Autores

Catia S P Silva (Autor) Outra; Andre R S Marcal (Autor) FCUP; Marta A Pereira (Autor) Outra; Teresa Mendonca (Autor) FCUP; Jorge Rozeira (Autor) Outra

Ata de Conferência Internacional

Título: IMAGE ANALYSIS AND RECOGNITION, PT II

Páginas: 268-277

9th International Conference on Image Analysis and Recognition (ICIAR)

Aveiro, PORTUGAL, JUN 25-27, 2012

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 7 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-005-K1H

DOI: 10.1007/978-3-642-31298-4_32

Abstract (EN): 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 standard approach in automatic dermoscopic image analysis has usually three stages: (i) segmentation, (ii) feature extraction and selection, (iii) lesion classification. This paper evaluates the potential of an alternative approach based on the Menzies method presence of 1 or more of 6 color classes, indicating that the lesion should be considered a potential melanoma. This method does not require stages (i) and (ii) - lesion segmentation and feature extraction. The Jeffries-Matusita and Transformed Divergence metrics were used to evaluate the color class separability. The preliminary results presented in this paper suggest that a system based on the Menzies method could provide valuable information for automatic dermoscopic image analysis.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10