A novel approach to segment skin lesions in dermoscopic images based on a deformable model

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

Autores

Zhen Ma (Autor) FEUP; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: IEEE Journal of Biomedical and Health Informatics

Vol. 20 Nº 2

Páginas: 615-623

ISSN: 2168-2194

Editora: IEEE

Indexação

ISI Web of Knowledge - 41 Citações

ISI Web of Science

Scopus - 98 Citações

INSPEC

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências médicas e da saúde

Outras Informações

ID Authenticus: P-00K-AN9

Abstract (EN): Abstract: Dermoscopy is an imaging technique that has been widely used in the diagnosis of skin lesions. However, its accuracy largely depends on the dermatologist's experience; thus, computer-aided diagnosis techniques are required. In this paper, a novel approach based on a deformable model is proposed to handle the segmentation of skin lesions in dermoscopic images. The RGB color space is converted so that the color information contained in the images can be used effectively to differentiate normal skin and skin lesions; and the differences in the color channels are combined together to define the speed function and the stopping criterion of the deformable model. This novel approach is robust against the noise, and provides an effective and flexible segmentation. Two image databases were used to test the performance of the novel approach and the segmentation results obtained were satisfactory. Quantitative analysis on 250 dermoscopic images showed that the novel algorithm outperformed other state-of-the-art algorithms. Also, using comparative data, the reliability and the implementation issues of the approach are discussed in this paper.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9