A computational approach for detecting pigmented skin lesions in macroscopic images

• Tipo: Artigo em Revista Científica Internacional
• Data: 2016

Autores

Roberta B. Oliveira (Autor) FEUP; Norian Marranghello (Autor) Outra; Aledir S. Pereira (Autor) Outra; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: Expert Systems with Applications

Vol. 61

Páginas: 53-63

ISSN: 0957-4174

Editora: Elsevier

Indexação

ISI Web of Knowledge - 38 Citações

ISI Web of Science

Scopus - 60 Citações

INSPEC

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências da engenharia e tecnologias

Outras Informações

ID Authenticus: P-00K-GFV

DOI: 10.1016/j.eswa.2016.05.017

Abstract (EN): Skin cancer is considered one of the most common types of cancer in several countries and its incidence rate has increased in recent years. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. Computational analysis of skin lesion images has become a challenging research area due to the difficulty in discerning some types of skin lesions. A novel computational approach is presented for extracting skin lesion features from images based on asymmetry, border, colour and texture analysis, in order to diagnose skin lesion types. The approach is based on an anisotropic diffusion filter, an active contour model without edges and a support vector machine. Experiments were performed regarding the segmentation and classification of pigmented skin lesions in macroscopic images, with the results obtained being very promising.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11