Utilize este identificador para referenciar este registo:
https://hdl.handle.net/10216/94988
Autor(es): | Coimbra, M Riaz, F Areia, M Baldaque Silva, FB Dinis Ribeiro, M |
Título: | Segmentation for Classification of Gastroenterology Images |
Data de publicação: | 2010 |
Resumo: | Automatic classification of cancer lesions in tissues observed using gastroenterology imaging is a non-trivial pattern recognition task involving filtering, segmentation, feature extraction and classification. In this paper we measure the impact of a variety of segmentation algorithms (mean shift, normalized cuts, level-sets) on the automatic classification performance of gastric tissue into three classes: cancerous, precancerous and normal. Classification uses a combination of color (hue-saturation histograms) and texture (local binary patterns) features, applied to two distinct imaging modalities: chromoendoscopy and narrow-band imaging. Results show that mean-shift obtains an interesting performance for both scenarios producing low classification degradations (6%), full image classification is highly inaccurate reinforcing the importance of segmentation research for Gastroenterology, and confirm that Patch Index is an interesting measure of the classification potential of small to medium segmented regions. |
Assunto: | Ciência de computadores, Biotecnologia ambiental Computer science, Environmental biotechnology |
Áreas do conhecimento: | Ciências da engenharia e tecnologias::Biotecnologia ambiental Engineering and technology::Environmental biotechnology |
URI: | https://repositorio-aberto.up.pt/handle/10216/94988 |
Fonte: | 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 |
Tipo de Documento: | Artigo em Livro de Atas de Conferência Internacional |
Condições de Acesso: | restrictedAccess |
Aparece nas coleções: | FCUP - Artigo em Livro de Atas de Conferência Internacional FMUP - Artigo em Livro de Atas de Conferência Internacional |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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48304.pdf Restricted Access | Artigo | 970.48 kB | Adobe PDF | Request a copy from the Author(s) |
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