Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusion
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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Title
Giga-voxel multidimensional fluorescence imaging combining single-pixel detection and data fusionAuthor (s)
Date
2021-08-27Publisher
Optical Society of AmericaISSN
0146-9592; 1539-4794Bibliographic 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)Type
info:eu-repo/semantics/articleVersion
info:eu-repo/semantics/acceptedVersionSubject
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 ... [+]
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. [-]
Is part of
Optics Letters Vol. 46, Issue 17, (2021)Funder Name
Ministerio de Ciencia, Innovación y Universidades | Regione Lombardia | Universitat Jaume I | Generalitat Valenciana | Laserlab–Europe
Project code
PID2019-110927RB-I00 / AEI / 10.13039/501100011033 | NEWMED, POR FESR 2014-2020 | UJIB2018-68 | PROMETEO/2020/029, ACIF/2019/019 | 654148, Horizon 2020, CUSBO002482
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info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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