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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Capdehourat, Germán | es |
dc.contributor.author | Corez, Andrés | es |
dc.contributor.author | Bazzano, Anabella | es |
dc.contributor.author | Musé, Pablo | es |
dc.date.accessioned | 2023-08-01T20:33:10Z | - |
dc.date.available | 2023-08-01T20:33:10Z | - |
dc.date.issued | 2009 | es |
dc.date.submitted | 20230801 | es |
dc.identifier.citation | Capdehourat, G, Corez, A, Bazzano, A, Musé, P. “Pigmented skin lesions classification using dermatoscopic images”. Bayro-Corrochano E., Eklundh JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer. . https://doi.org/10.1007/978-3-642-10268-4_63 | es |
dc.identifier.uri | https://hdl.handle.net/20.500.12008/38646 | - |
dc.description.abstract | In this paper we propose a machine learning approach to classify melanocytic lesions in malignant and benign from dermatoscopic images. The image database is composed of 433 benign lesions and 80 malignant melanoma. After an image pre-processing stage that includes hair removal filtering, each image is automatically segmented using well known image segmentation algorithms. Then, each lesion is characterized by a feature vector that contains shape, color and texture information, as well as local and global parameters that try to reflect structures used in medical diagnosis. The learning and classification stage is performed using AdaBoost.M1 with C4.5 decision trees. For the automatically segmented database, classification delivered a false positive rate of 8.75% for a sensitivity of 95%. The same classification procedure applied to manually segmented images by an experienced dermatologist yielded a false positive rate of 4.62% for a sensitivity of 95%. | es |
dc.language | en | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Bayro-Corrochano E., Eklundh JO. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2009. Lecture Notes in Computer Science, vol 5856. Springer. | es |
dc.rights | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
dc.title | Pigmented skin lesions classification using dermatoscopic images | es |
dc.type | Preprint | es |
dc.rights.licence | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
dc.identifier.doi | https://doi.org/10.1007/978-3-642-10268-4_63 | es |
Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
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CCBM09.pdf | 1,4 MB | Adobe PDF | Visualizar/Abrir |
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