Super-resolution time-resolved imaging using computational sensor fusion

Callenberg, C., Lyons, A. , den Brok, D., Fatima, A., Turpin, A. , Zickus, V., Machesky, L. , Whitelaw, J., Faccio, D. and Hullin, M.B. (2021) Super-resolution time-resolved imaging using computational sensor fusion. Scientific Reports, 11, 1689. (doi: 10.1038/s41598-021-81159-x) (PMID:33462284) (PMCID:PMC7813875)

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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 12×12, and demonstrating up to 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.

Item Type:Articles
Additional Information:The authors acknowledge funding from EPSRC (UK, grant no. EP/T00097X/1 and EP/T002123/1) and the European Research Council (ERC Starting Grant "ECHO"). DF is supported by the Royal Academy of Engineering under the Chairs in Emerging Technologies scheme.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Faccio, Professor Daniele and Fatima, Dr Areeba and Machesky, Professor Laura and Zickus, Dr Vytautas and Turpin, Dr Alejandro and Lyons, Dr Ashley
Authors: Callenberg, C., Lyons, A., den Brok, D., Fatima, A., Turpin, A., Zickus, V., Machesky, L., Whitelaw, J., Faccio, D., and Hullin, M.B.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Physics and Astronomy
Journal Name:Scientific Reports
Publisher:Nature Research
ISSN:2045-2322
ISSN (Online):2045-2322
Copyright Holders:Copyright © The Author(s) 2021
First Published:First published in Scientific Reports 11:1689
Publisher Policy:Reproduced under a Creative Commons license

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
305567QuantIC - The UK Quantum Technoogy Hub in Quantum Enhanced ImagingMiles PadgettEngineering and Physical Sciences Research Council (EPSRC)EP/T00097X/1P&S - Physics & Astronomy
306629Harnessing the physics of light to reveal mechanisms of multicellular shape and movementLaura MacheskyEngineering and Physical Sciences Research Council (EPSRC)EP/T002123/1ENG - Biomedical Engineering
305153RAEng Chair Emerging TechnologiesDaniele FaccioRoyal Academy of Engineering (RAE)CiET1819/20P&S - Physics & Astronomy