Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/58307
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fabelo Gómez, Himar Antonio | en_US |
dc.contributor.author | Halicek, Martin | en_US |
dc.contributor.author | Ortega Sarmiento, Samuel | en_US |
dc.contributor.author | Zbigniew Szolna,Adam | en_US |
dc.contributor.author | Morera Molina, Jesús Manuel | en_US |
dc.contributor.author | Sarmiento Rodríguez, Roberto | en_US |
dc.contributor.author | Marrero Callicó, Gustavo Iván | en_US |
dc.contributor.author | Fei, Baowei | en_US |
dc.contributor.editor | Linte, Cristian A. | - |
dc.contributor.editor | Fei, Baowei | - |
dc.date.accessioned | 2019-12-10T17:24:35Z | - |
dc.date.available | 2019-12-10T17:24:35Z | - |
dc.date.issued | 2019 | en_US |
dc.identifier.isbn | 9781510625495 | - |
dc.identifier.issn | 1605-7422 | en_US |
dc.identifier.other | Scopus | - |
dc.identifier.other | WoS | - |
dc.identifier.uri | http://hdl.handle.net/10553/58307 | - |
dc.description.abstract | Brain cancer surgery has the goal of performing an accurate resection of the tumor and preserving as much as possible the quality of life of the patient. There is a clinical need to develop non-invasive techniques that can provide reliable assistance for tumor resection in real-time during surgical procedures. Hyperspectral imaging (HSI) arises as a new, noninvasive and non-ionizing technique that can assist neurosurgeons during this difficult task. In this paper, we explore the use of deep learning (DL) techniques for processing hyperspectral (HS) images of in-vivo human brain tissue. We developed a surgical aid visualization system capable of offering guidance to the operating surgeon to achieve a successful and accurate tumor resection. The employed HS database is composed of 26 in-vivo hypercubes from 16 different human patients, among which 258,810 labelled pixels were used for evaluation. The proposed DL methods achieve an overall accuracy of 95% and 85% for binary and multiclass classifications, respectively. The proposed visualization system is able to generate a classification map that is formed by the combination of the DL map and an unsupervised clustering via a majority voting algorithm. This map can be adjusted by the operating surgeon to find the suitable configuration for the current situation during the surgical procedure. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Progress in Biomedical Optics and Imaging - Proceedings of SPIE | en_US |
dc.source | Progress in Biomedical Optics and Imaging - Proceedings of SPIE [ISSN 1605-7422], v. 10951, 1095110 | en_US |
dc.subject | 3314 Tecnología médica | en_US |
dc.subject.other | Brain Shift | en_US |
dc.subject.other | Resection | en_US |
dc.subject.other | Extent | en_US |
dc.subject.other | Brain Tumor | en_US |
dc.subject.other | Cancer Surgery | en_US |
dc.subject.other | Hyperspectral Imaging | en_US |
dc.subject.other | Intraoperative Imaging | en_US |
dc.subject.other | Deep Learning | en_US |
dc.subject.other | Supervised Classification | en_US |
dc.subject.other | Convolutional Neural Network (Cnn) | en_US |
dc.subject.other | Classifier | en_US |
dc.title | Surgical aid visualization system for glioblastoma tumor identification based on deep learning and in-vivo hyperspectral images of human patients | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.type | Article | en_US |
dc.relation.conference | Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling | - |
dc.identifier.doi | 10.1117/12.2512569 | en_US |
dc.identifier.scopus | 85068937866 | - |
dc.identifier.isi | 000483683500035 | - |
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.authorscopusid | 56405568500 | - |
dc.contributor.authorscopusid | 56285163800 | - |
dc.contributor.authorscopusid | 57189334144 | - |
dc.contributor.authorscopusid | 14032568700 | - |
dc.contributor.authorscopusid | 35466252100 | - |
dc.contributor.authorscopusid | 35609452100 | - |
dc.contributor.authorscopusid | 56006321500 | - |
dc.contributor.authorscopusid | 7005499116 | - |
dc.identifier.eissn | 1996-756X | - |
dc.description.firstpage | 35 | en_US |
dc.relation.volume | 10951 | en_US |
dc.investigacion | Ciencias de la Salud | en_US |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.contributor.daisngid | 2096372 | - |
dc.contributor.daisngid | 6051182 | - |
dc.contributor.daisngid | 1812298 | - |
dc.contributor.daisngid | 2864016 | - |
dc.contributor.daisngid | 5142172 | - |
dc.contributor.daisngid | 116294 | - |
dc.contributor.daisngid | 506422 | - |
dc.contributor.daisngid | 306847 | - |
dc.description.notas | SPIE Medical Imaging, 2019, San Diego, California, United States | en_US |
dc.description.numberofpages | 11 | en_US |
dc.utils.revision | No | en_US |
dc.contributor.wosstandard | Linte, Cristian A. | - |
dc.contributor.wosstandard | Fei, Baowei | - |
dc.contributor.wosstandard | WOS:Fabelo, H | - |
dc.contributor.wosstandard | WOS:Halicek, M | - |
dc.contributor.wosstandard | WOS:Ortega, S | - |
dc.contributor.wosstandard | WOS:Szolna, A | - |
dc.contributor.wosstandard | WOS:Morera, J | - |
dc.contributor.wosstandard | WOS:Sarmiento, R | - |
dc.contributor.wosstandard | WOS:Callico, GM | - |
dc.contributor.wosstandard | WOS:Fei, BW | - |
dc.identifier.conferenceid | events121169 | - |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-ING | en_US |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.author.dept | GIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos | - |
crisitem.author.dept | IU de Microelectrónica Aplicada | - |
crisitem.author.dept | GIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos | - |
crisitem.author.dept | IU de Microelectrónica Aplicada | - |
crisitem.author.dept | GIR SIANI: Ingeniería biomédica aplicada a estimulación neural y sensorial | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.dept | Departamento de Ciencias Médicas y Quirúrgicas | - |
crisitem.author.dept | GIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos | - |
crisitem.author.dept | IU de Microelectrónica Aplicada | - |
crisitem.author.dept | Departamento de Ingeniería Electrónica y Automática | - |
crisitem.author.dept | GIR IUMA: Diseño de Sistemas Electrónicos Integrados para el procesamiento de datos | - |
crisitem.author.dept | IU de Microelectrónica Aplicada | - |
crisitem.author.dept | Departamento de Ingeniería Electrónica y Automática | - |
crisitem.author.orcid | 0000-0002-9794-490X | - |
crisitem.author.orcid | 0000-0002-7519-954X | - |
crisitem.author.orcid | 0000-0002-4843-0507 | - |
crisitem.author.orcid | 0000-0002-3784-5504 | - |
crisitem.author.parentorg | IU de Microelectrónica Aplicada | - |
crisitem.author.parentorg | IU de Microelectrónica Aplicada | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.parentorg | IU de Microelectrónica Aplicada | - |
crisitem.author.parentorg | IU de Microelectrónica Aplicada | - |
crisitem.author.fullName | Fabelo Gómez, Himar Antonio | - |
crisitem.author.fullName | Ortega Sarmiento,Samuel | - |
crisitem.author.fullName | Zbigniew Szolna,Adam | - |
crisitem.author.fullName | Morera Molina, Jesús Manuel | - |
crisitem.author.fullName | Sarmiento Rodríguez, Roberto | - |
crisitem.author.fullName | Marrero Callicó, Gustavo Iván | - |
crisitem.event.eventsstartdate | 17-02-2019 | - |
crisitem.event.eventsenddate | 19-02-2019 | - |
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