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Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion
dc.contributor.author | Soldevila, Fernando | |
dc.contributor.author | Lenz, Armin | |
dc.contributor.author | Ghezzi, Alberto | |
dc.contributor.author | Farina, Andrea | |
dc.contributor.author | D'Andrea, Cosimo | |
dc.contributor.author | Tajahuerce, Enrique | |
dc.date.accessioned | 2021-10-14T12:13:22Z | |
dc.date.available | 2021-10-14T12:13:22Z | |
dc.date.issued | 2021-08-27 | |
dc.identifier.citation | F. Soldevila, A. J. M. Lenz, A. Ghezzi, A. Farina, C. D’Andrea, and E. Tajahuerce, "Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion," Opt. Lett. 46, 4312-4315 (2021) | ca_CA |
dc.identifier.issn | 0146-9592 | |
dc.identifier.issn | 1539-4794 | |
dc.identifier.uri | http://hdl.handle.net/10234/195010 | |
dc.description.abstract | Time-resolved fluorescence imaging is a key tool in biomedical applications, as it allows to non-invasively obtain functional and structural information. However, the big amount of collected data introduces challenges in both acquisition speed and processing needs. Here, we introduce a novel technique that allows to acquire a giga-voxel 4D hypercube in a fast manner while measuring only 0.03% of the dataset. The system combines two single-pixel cameras and a conventional 2D array detector working in parallel. Data fusion techniques are introduced to combine the individual 2D and 3D projections acquired by each sensor in the final high-resolution 4D hypercube, which can be used to identify different fluorophore species by their spectral and temporal signatures. | ca_CA |
dc.format.extent | 5 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Optical Society of America | ca_CA |
dc.relation.isPartOf | Optics Letters Vol. 46, Issue 17, (2021) | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | ca_CA |
dc.subject | fluorescence | ca_CA |
dc.title | Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1364/OL.434127 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.type.version | info:eu-repo/semantics/acceptedVersion | ca_CA |
project.funder.name | Ministerio de Ciencia, Innovación y Universidades | ca_CA |
project.funder.name | Regione Lombardia | ca_CA |
project.funder.name | Universitat Jaume I | ca_CA |
project.funder.name | Generalitat Valenciana | ca_CA |
project.funder.name | Laserlab–Europe | ca_CA |
oaire.awardNumber | PID2019-110927RB-I00 / AEI / 10.13039/501100011033 | ca_CA |
oaire.awardNumber | NEWMED, POR FESR 2014-2020 | ca_CA |
oaire.awardNumber | UJIB2018-68 | ca_CA |
oaire.awardNumber | PROMETEO/2020/029, ACIF/2019/019 | ca_CA |
oaire.awardNumber | 654148, Horizon 2020, CUSBO002482 | ca_CA |
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