Utilize este identificador para referenciar este registo: https://hdl.handle.net/10216/69073
Autor(es): Zhen Ma
João Manuel R. S. Tavares
Título: Current trends of segmentation algorithms for skin lesions
Data de publicação: 2013
Resumo: Skin cancer has become one of the most frequent forms of cancer nowadays; its high prevalence has attracted many studies towards the causes and treatments in the recent years. However, the current practice of detecting skin cancers is fairly subjective and may suffer from diagnostic errors. In order to solve this problem, an effective computer-aided diagnosis (CAD) system is urgently demanded. Such system can provide an objective source to help the dermatologist improve the diagnostic accuracy. Such an automated system aims to detect the skin lesions on the acquired images and then analyzes whether those lesions are benign or malignant. The usual computational procedure is composed of three steps: image segmentation, feature extraction, and classification. Among these steps, the segmentation has deterministic influences to the later quantitative analysis and classification; however, due to the complicated appearance of skin lesions in the images, correct segmentation of their boundaries is very challenging. Many algorithms have been proposed to fulfill this task, and some of them have achieved satisfactory performances. Nevertheless, the performance of the existing algorithms still needs further improvement to be accepted in clinical practice. This paper will review these algorithms and summarize their trends of the development; algorithms focused in this work contain both the ones for dermoscopic images and the ones for macroscopic images. Advantages and disadvantages of each algorithm will be discussed; and possible techniques that can be used for improvement will be proposed. Open image database will be used for testing and for the illustration and comparisons among the different algorithms.
Assunto: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Áreas do conhecimento: Ciências da engenharia e tecnologias
Engineering and technology
URI: https://hdl.handle.net/10216/69073
Fonte: ICCEBS2013 - International Conference on Computational and Experimental Biomedical Sciences
Tipo de Documento: Artigo em Livro de Atas de Conferência Internacional
Condições de Acesso: openAccess
Licença: https://creativecommons.org/licenses/by-nc/4.0/
Aparece nas coleções:FEUP - Artigo em Livro de Atas de Conferência Internacional

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