Band selection in spectral imaging for non-invasive melanoma diagnosis
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Otros documentos de la autoría: Quinzán, Ianisse; Martínez Sotoca, José; Latorre Carmona, Pedro; Pla, Filiberto; García-Sevilla, Pedro; Boldó, Enrique
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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INVESTIGACIONMetadatos
Título
Band selection in spectral imaging for non-invasive melanoma diagnosisAutoría
Fecha de publicación
2013-03-04Editor
Optical Society of AmericaISSN
2156-7085Cita bibliográfica
QUINZÁN, Ianisse, et al. Band selection in spectral imaging for non-invasive melanoma diagnosis. Biomedical optics express, 2013, vol. 4, no 4, p. 514-519Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.opticsinfobase.org/boe/abstract.cfm?uri=boe-4-4-514Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
A method consisting of the combination of the Synthetic Minority Over-Sampling TEchnique (SMOTE) and the Sequential Forward Floating Selection (SFFS) technique is used to do band selection in a highly imbalanced, small ... [+]
A method consisting of the combination of the Synthetic Minority Over-Sampling TEchnique (SMOTE) and the Sequential Forward Floating Selection (SFFS) technique is used to do band selection in a highly imbalanced, small size, two-class multispectral dataset of melanoma and non-melanoma lesions. The aim is to improve classification rate and help to identify those spectral bands that have a more important role in melanoma detection. All the processing steps were designed taking into account the low number of samples in the dataset, situation that is quite common in medical cases. The training/test sets are built using a Leave-One-Out strategy. SMOTE is applied in order to deal with the imbalance problem, together with the Qualified Majority Voting scheme (QMV). Support Vector Machines (SVM) is the classification method applied over each balanced set. Results indicate that all melanoma lesions are correctly classified, using a low number of bands, reaching 100% sensitivity and 72% specificity when considering nine (out of a total of 55) spectral bands. [-]
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Biomedical Optics Express, 2013, vol. 4, no. 4Derechos de acceso
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