Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/69248
Campo DC Valoridioma
dc.contributor.authorCampos-Delgado, Daniel U.en_US
dc.contributor.authorGutierrez-Navarro, Omaren_US
dc.contributor.authorRico-Jimenez, Jose J.en_US
dc.contributor.authorDuran-Sierra, Elvisen_US
dc.contributor.authorFabelo Gómez, Himar Antonioen_US
dc.contributor.authorOrtega Sarmiento, Samuelen_US
dc.contributor.authorMarrero Callicó, Gustavo Ivánen_US
dc.contributor.authorJo, Javier A.en_US
dc.date.accessioned2020-01-23T09:23:42Z-
dc.date.available2020-01-23T09:23:42Z-
dc.date.issued2019en_US
dc.identifier.issn2169-3536en_US
dc.identifier.urihttp://hdl.handle.net/10553/69248-
dc.description.abstractIn some applications of biomedical imaging, a linear mixture model can represent the constitutive elements (end-members) and their contributions (abundances) per pixel of the image. In this work, the extended blind end-member and abundance extraction (EBEAE) methodology is mathematically formulated to address the blind linear unmixing (BLU) problem subject to positivity constraints in optical measurements. The EBEAE algorithm is based on a constrained quadratic optimization and an alternated least-squares strategy to jointly estimate end-members and their abundances. In our proposal, a local approach is used to estimate the abundances of each end-member by maximizing their entropy, and a global technique is adopted to iteratively identify the end-members by reducing the similarity among them. All the cost functions are normalized, and four initialization approaches are suggested for the end-members matrix. Synthetic datasets are used first for the EBEAE validation at different noise types and levels, and its performance is compared to state-of-the-art algorithms in BLU. In a second stage, three experimental biomedical imaging applications are addressed with EBEAE: M-FLIM for chemometric analysis in oral cavity samples, OCT for macrophages identification in post-mortem artery samples, and hyper-spectral images for in-vivo brain tissue classification and tumor identification. In our evaluations, EBEAE was able to provide a quantitative analysis of the samples with none or minimal a priori information.en_US
dc.languageengen_US
dc.relationIdentificación Hiperespectral de Tumores Cerebrales (Ithaca)en_US
dc.relation.ispartofIEEE Accessen_US
dc.sourceIEEE Access [ISSN 2169-3536], v. 7, p. 178539 - 178552en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherBlind linear unmixingen_US
dc.subject.otherConstrained optimizationen_US
dc.subject.otherFluorescence lifetime imaging microscopyen_US
dc.subject.otherHyperspectral imagingen_US
dc.subject.otherOptical coherence tomographyen_US
dc.titleExtended Blind End-Member and Abundance Extraction for Biomedical Imaging Applicationsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ACCESS.2019.2958985
dc.identifier.scopus85077221616
dc.identifier.isi000509483800094
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.authorscopusid57207809029
dc.contributor.authorscopusid13604892600
dc.contributor.authorscopusid55675508600
dc.contributor.authorscopusid57204668879
dc.contributor.authorscopusid56405568500
dc.contributor.authorscopusid57213070492
dc.contributor.authorscopusid56006321500
dc.contributor.authorscopusid7102413227
dc.description.lastpage178552-
dc.description.firstpage178539-
dc.relation.volume7-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.contributor.daisngid319674
dc.contributor.daisngid34862129
dc.contributor.daisngid31868083
dc.contributor.daisngid34875625
dc.contributor.daisngid34770098
dc.contributor.daisngid31939674
dc.contributor.daisngid506422
dc.contributor.daisngid369864
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Campos-Delgado, DU
dc.contributor.wosstandardWOS:Gutierrez-Navarro, O
dc.contributor.wosstandardWOS:Rico-Jimenez, JJ
dc.contributor.wosstandardWOS:Duran-Sierra, E
dc.contributor.wosstandardWOS:Fabelo, H
dc.contributor.wosstandardWOS:Ortega, S
dc.contributor.wosstandardWOS:Callico, G
dc.contributor.wosstandardWOS:Jo, JA
dc.date.coverdate2019
dc.identifier.ulpgces
dc.description.sjr0,775
dc.description.jcr3,745
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.project.principalinvestigatorMarrero Callicó, Gustavo Iván-
crisitem.author.deptGIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptGIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptGIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos-
crisitem.author.deptIU de Microelectrónica Aplicada-
crisitem.author.deptDepartamento de Ingeniería Electrónica y Automática-
crisitem.author.orcid0000-0002-9794-490X-
crisitem.author.orcid0000-0002-7519-954X-
crisitem.author.orcid0000-0002-3784-5504-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.parentorgIU de Microelectrónica Aplicada-
crisitem.author.fullNameFabelo Gómez, Himar Antonio-
crisitem.author.fullNameOrtega Sarmiento,Samuel-
crisitem.author.fullNameMarrero Callicó, Gustavo Iván-
Colección:Artículos
miniatura
pdf
Adobe PDF (19,67 MB)
Vista resumida

Citas SCOPUSTM   

25
actualizado el 30-mar-2025

Citas de WEB OF SCIENCETM
Citations

14
actualizado el 30-mar-2025

Visitas

73
actualizado el 30-dic-2023

Descargas

128
actualizado el 30-dic-2023

Google ScholarTM

Verifica

Altmetric


Comparte



Exporta metadatos



Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.