Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/17770
Título: | Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients |
Autor(es): | Martins, Maria M. Barbosa, Daniel Ramos, Jaime Lima, C. S. |
Palavras-chave: | Capsule endoscopy Discrete curvelet transform Gaussian mixture model Small bowell tumor |
Data: | 2010 |
Editora: | IEEE |
Revista: | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
Citação: | M. M. Martins, D. J. Barbosa, J. Ramos and C. S. Lima, "Small bowel tumors detection in capsule endoscopy by Gaussian modeling of Color Curvelet Covariance coefficients," 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, 2010, pp. 5557-5560, doi: 10.1109/IEMBS.2010.5626780. |
Resumo(s): | This paper is concerned with the classification of tumoral tissue in the small bowel by using capsule endoscopic images. The followed approach is based on texture classification. Texture descriptors are derived from selected scales of the Discrete Curvelet Transform (DCT). The goal is to take advantage of the high directional sensitivity of the DCT (16 directions) when compared with the Discrete Wavelet Transform (DWT) (3 directions). Second order statistics are then computed in the HSV color space and named Color Curvelet Covariance (3C) coefficients. Finally, these coefficients are modeled by a Gaussian Mixture Model (GMM). Sensitivity of 99% and specificity of 95.19% are obtained in the testing set. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/17770 |
ISBN: | 978-1-4244-4123-5 |
DOI: | 10.1109/IEMBS.2010.5626780 |
ISSN: | 1557-170X |
Versão da editora: | https://ieeexplore.ieee.org/document/5626780 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DEI - Artigos em atas de congressos internacionais |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Artigo_CE2.pdf | Documento principal | 539,13 kB | Adobe PDF | Ver/Abrir |