dc.creator | Acha Piñero, Begoña | es |
dc.creator | Serrano Gotarredona, María del Carmen | es |
dc.creator | Acha Catalina, José Ignacio | es |
dc.creator | Roa Romero, Laura María | es |
dc.date.accessioned | 2017-03-29T14:21:01Z | |
dc.date.available | 2017-03-29T14:21:01Z | |
dc.date.issued | 2005 | |
dc.identifier.citation | Acha Piñero, B., Serrano Gotarredona, M.d.C., Acha Catalina, J.I. y Roa Romero, L.M. (2005). Segmentation and classification of burn images by color and texture information. Journal of Biomedical Optics, 10 (3), 034014-1-034014-11. | |
dc.identifier.issn | 10833668 | es |
dc.identifier.uri | http://hdl.handle.net/11441/56541 | |
dc.description.abstract | In this paper, a burn color image segmentation and classification
system is proposed. The aim of the system is to separate burn
wounds from healthy skin, and to distinguish among the different
types of burns (burn depths). Digital color photographs are used as
inputs to the system. The system is based on color and texture information,
since these are the characteristics observed by physicians in
order to form a diagnosis. A perceptually uniform color space
(L *u*v *) was used, since Euclidean distances calculated in this
space correspond to perceptual color differences. After the burn is
segmented, a set of color and texture features is calculated that serves
as the input to a Fuzzy-ARTMAP neural network. The neural network
classifies burns into three types of burn depths: superficial dermal,
deep dermal, and full thickness. Clinical effectiveness of the method
was demonstrated on 62 clinical burn wound images, yielding an
average classification success rate of 82% | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Spie-soc photo-optical instrumentation engineers | es |
dc.relation.ispartof | Journal of Biomedical Optics, 10 (3), 034014-1-034014-11. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | color images | es |
dc.subject | burn | es |
dc.subject | image segmentation | es |
dc.subject | burn classification | es |
dc.title | Segmentation and classification of burn images by color and texture information | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.publisherversion | http://0-eds.b.ebscohost.com.fama.us.es/eds/detail/detail?sid=b5ab6bed-343e-4dc2-906a-c92dc1ad145f%40sessionmgr104&vid=0&hid=119&bdata=Jmxhbmc9ZXMmc2l0ZT1lZHMtbGl2ZSZzY29wZT1zaXRl#AN=000235127400034&db=edswsc | es |
dc.identifier.doi | 10.1117/1.1921227 | es |
idus.format.extent | 11 p. | es |
dc.journaltitle | Journal of biomedical optics | es |
dc.publication.volumen | 10 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 034014-1 | es |
dc.publication.endPage | 034014-11 | es |