Evaluation of the Menzies method potential for automatic dermoscopic image analysis

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

Autores

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

Ata de Conferência Internacional

Título: Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III

Páginas: 103-108

International Symposium CompIMAGE 2012 Rome, Italy 5-7 September 2012

Rome, Italy, 5-7 September 2012

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Classificação Científica

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

Outras Informações

ID Authenticus: P-00G-HTD

DOI: 10.1201/b12753-19

Abstract (EN): There is a considerable interest in the development of automatic image analysis systems for dermoscopic images. The standard approach usually consists of three stages: (i) image segmentation, (ii) feature extraction and selection, and (iii) lesion classification. This paper evaluates the potential of an alternative approach, based on the Menzies method. It consists on the identification of the presence of 1 or more of 6 possible color classes, indicating that the lesion should be considered a potential melanoma. The Jeffries-Matusita (JM) and Transformed Divergence (TD) separability measures were used for an experimental evaluation with 28 dermoscopic images. In the most challenging case tested, with training identified in multiple images, 8 out of 15 class pairs were found to be well separable, or 13+ 2 out of 21 considering the skin as an additional class.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6