Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/63415
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dc.contributor.authorFabelo Gómez, Himar Antonioen_US
dc.contributor.authorCarretero, Gregorioen_US
dc.contributor.authorAlmeida, Pabloen_US
dc.contributor.authorGarcia, Adayen_US
dc.contributor.authorHernandez González, Javier Adayen_US
dc.contributor.authorGodtliebsen, Freden_US
dc.contributor.authorMelian, Veronicaen_US
dc.contributor.authorMartinez, Beatrizen_US
dc.contributor.authorBeltran, Patriciaen_US
dc.contributor.authorOrtega, Samuelen_US
dc.contributor.authorMele Marrero, Margaritaen_US
dc.contributor.authorMarrero Callicó, Gustavo Ivánen_US
dc.contributor.authorSarmiento Rodríguez, Robertoen_US
dc.contributor.authorCastano, Ireneen_US
dc.date.accessioned2020-01-22T09:53:43Z-
dc.date.available2020-01-22T09:53:43Z-
dc.date.issued2019en_US
dc.identifier.isbn978-1-7281-5459-6en_US
dc.identifier.issn2471-6170en_US
dc.identifier.urihttp://hdl.handle.net/10553/63415-
dc.description.abstractThis paper presents the development of a dermatological acquisition system based on hyperspectral (HS) imaging for the assistance in the diagnosis of pigmented skin lesions (PSLs). The developed system is able to capture HS images of 50×50 pixels and 125 spectral bands in the VNIR (Visual and Near Infrared) region between 450 and 950 nm, using a cold light halogen illumination device. The system is able to capture images of a size of 12×12 mm in less than 1 second. Employing this system, a preliminary database of 49 HS images of PSLs from 36 patients was generated. The data was labeled in four different classes and classified using a supervised machine learning method optimized by means of a genetic algorithm. The results obtained in these preliminary experiments demonstrate the potential of the developed system to perform a rapid and accurate assistance in the skin cancer diagnosis task during clinical routine practiceen_US
dc.languageengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relationIdentificación Hiperespectral de Tumores Cerebrales (Ithaca)en_US
dc.relationPlataforma H2/Sw Distribuida Para El Procesamiento Inteligente de Información Sensorial Heterogenea en Aplicaciones de Supervisión de Grandes Espacios Naturalesen_US
dc.source2019 XXXIV Conference on Design of Circuits and Integrated Systems (DCIS 2019)en_US
dc.subject3314 Tecnología médicaen_US
dc.titleDermatologic Hyperspectral Imaging System for Skin Cancer Diagnosis Assistanceen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeconferenceObjecten_US
dc.relation.conference34th Conference on Design of Circuits and Integrated Systems, DCIS 2019en_US
dc.identifier.doi10.1109/DCIS201949030.2019.8959869en_US
dc.description.lastpage6en_US
dc.description.firstpage1en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INGen_US
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.event.eventsstartdate20-11-2019-
crisitem.event.eventsenddate22-11-2019-
crisitem.author.deptIUMA Sistemas de Información y Comunicaciones-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.deptIUMA Sistemas de Información y Comunicaciones-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.orcid0000-0002-9794-490X-
crisitem.author.orcid0000-0002-3784-5504-
crisitem.author.orcid0000-0002-4843-0507-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.fullNameFabelo Gómez, Himar Antonio-
crisitem.author.fullNameMele Marrero, Margarita-
crisitem.author.fullNameMarrero Callicó, Gustavo Iván-
crisitem.author.fullNameSarmiento Rodríguez, Roberto-
Appears in Collections:Actas de congresos
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