Super-resolution time-resolved imaging using computational sensor fusion

Abstract Imaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of...

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Autores principales:	C. Callenberg, A. Lyons, D. den Brok, A. Fatima, A. Turpin, V. Zickus, L. Machesky, J. Whitelaw, D. Faccio, M. B. Hullin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3e1b87eb10214096987243d291398579
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spelling	oai:doaj.org-article:3e1b87eb10214096987243d2913985792021-12-02T13:48:53ZSuper-resolution time-resolved imaging using computational sensor fusion10.1038/s41598-021-81159-x2045-2322https://doaj.org/article/3e1b87eb10214096987243d2913985792021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81159-xhttps://doaj.org/toc/2045-2322Abstract Imaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.C. CallenbergA. LyonsD. den BrokA. FatimaA. TurpinV. ZickusL. MacheskyJ. WhitelawD. FaccioM. B. HullinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q C. Callenberg A. Lyons D. den Brok A. Fatima A. Turpin V. Zickus L. Machesky J. Whitelaw D. Faccio M. B. Hullin Super-resolution time-resolved imaging using computational sensor fusion
description	Abstract Imaging across both the full transverse spatial and temporal dimensions of a scene with high precision in all three coordinates is key to applications ranging from LIDAR to fluorescence lifetime imaging. However, compromises that sacrifice, for example, spatial resolution at the expense of temporal resolution are often required, in particular when the full 3-dimensional data cube is required in short acquisition times. We introduce a sensor fusion approach that combines data having low-spatial resolution but high temporal precision gathered with a single-photon-avalanche-diode (SPAD) array with data that has high spatial but no temporal resolution, such as that acquired with a standard CMOS camera. Our method, based on blurring the image on the SPAD array and computational sensor fusion, reconstructs time-resolved images at significantly higher spatial resolution than the SPAD input, upsampling numerical data by a factor $$12 \times 12$$ 12 × 12 , and demonstrating up to $$4 \times 4$$ 4 × 4 upsampling of experimental data. We demonstrate the technique for both LIDAR applications and FLIM of fluorescent cancer cells. This technique paves the way to high spatial resolution SPAD imaging or, equivalently, FLIM imaging with conventional microscopes at frame rates accelerated by more than an order of magnitude.
format	article
author	C. Callenberg A. Lyons D. den Brok A. Fatima A. Turpin V. Zickus L. Machesky J. Whitelaw D. Faccio M. B. Hullin
author_facet	C. Callenberg A. Lyons D. den Brok A. Fatima A. Turpin V. Zickus L. Machesky J. Whitelaw D. Faccio M. B. Hullin
author_sort	C. Callenberg
title	Super-resolution time-resolved imaging using computational sensor fusion
title_short	Super-resolution time-resolved imaging using computational sensor fusion
title_full	Super-resolution time-resolved imaging using computational sensor fusion
title_fullStr	Super-resolution time-resolved imaging using computational sensor fusion
title_full_unstemmed	Super-resolution time-resolved imaging using computational sensor fusion
title_sort	super-resolution time-resolved imaging using computational sensor fusion
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3e1b87eb10214096987243d291398579
work_keys_str_mv	AT ccallenberg superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT alyons superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT ddenbrok superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT afatima superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT aturpin superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT vzickus superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT lmachesky superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT jwhitelaw superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT dfaccio superresolutiontimeresolvedimagingusingcomputationalsensorfusion AT mbhullin superresolutiontimeresolvedimagingusingcomputationalsensorfusion
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Super-resolution time-resolved imaging using computational sensor fusion

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