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dc.contributor.authorPardo Franco, Arturo 
dc.contributor.authorGutiérrez Gutiérrez, José Alberto 
dc.contributor.authorLópez Higuera, José Miguel 
dc.contributor.authorPogue, Brian Wiliam
dc.contributor.authorConde Portilla, Olga María 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2021-03-04T15:42:17Z
dc.date.available2021-03-04T15:42:17Z
dc.date.issued2020-02-19
dc.identifier.issn0277-786X
dc.identifier.issn1996-756X
dc.identifier.otherFIS2010-19860es_ES
dc.identifier.otherTEC2016-76021-C2-2-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/20857
dc.description.abstractThis work proposes separating data analysis from hyperspectral enhancement or editing, providing a robust, context-independent, fully-tunable framework for biomarker-based contrast in wide-field imaging with a series of reliable properties that could enable its use in guided surgery. Some applications of this method powered by deep learning diagnostics will be discussed and shown.es_ES
dc.description.sponsorshipSpanish Ministry of Science, Innovation and Universities (FIS2010-19860, TEC2016-76021-C2-2-R), Spanish Ministry of Economy, Industry and Competitiveness and Instituto de Salud Carlos III (DTS17-00055, DTS15- 00238), Instituto de Investigación Valdecilla (INNVAL16/02, INNVAL18/23), Spanish Ministry of Education, Culture, and Sports (FPU16/05705).es_ES
dc.format.extent5 p.es_ES
dc.language.isoenges_ES
dc.publisherSPIE Society of Photo-Optical Instrumentation Engineerses_ES
dc.rights© 2020 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.es_ES
dc.sourceProceedings of SPIE, 2020, 11222, 1122208es_ES
dc.sourceMolecular-Guided Surgery: Molecules, Devices, and Applications VI, San Francisco, California, 2020es_ES
dc.titleAffinity-based color enhancement methods for contrast enhancement in hyperspectral and multimodal imaginges_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1117/12.2546961es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1117/12.2546961
dc.type.versionpublishedVersiones_ES


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