Chemical Sensors with Deep Spatiotemporal Priors
T.-a. Pham, S. Mondal, A. Boquet-Pujadas, M. Unser, G. Barbastathis
Proceedings of the OSA Imaging and Applied Optics Congress on Computational Optical Sensing and Imaging (COSI'23), Boston MA, USA, August 14-17, 2023, paper no. CTu5B.5.
We propose a variational approach to recover concentration from raw fluorescence images of chemical sensors. This allows us to impose prior knowledge regarding the spatiotemporal distribution of the concentration while accounting for the sensor kinetics.
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AUTHOR="Pham, T.-a. and Mondal, S. and Boquet-Pujadas, A. and Unser, M.
and Barbastathis, G.",
TITLE="Chemical Sensors with Deep Spatiotemporal Priors",
BOOKTITLE="Proceedings of the {OSA} Imaging and Applied Optics Congress
on Computational Optical Sensing and Imaging ({COSI'23})",
YEAR="2023",
editor="",
volume="",
series="",
pages="",
address="Boston MA, USA",
month="August 14-17,",
organization="",
publisher="",
note="paper no.\ CTu5B.5")
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