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Event-driven acquisition for content-enriched microscopy

Dora Mahecic, View ORCID ProfileWilli L. Stepp, Chen Zhang, Juliette Griffié, View ORCID ProfileMartin Weigert, View ORCID ProfileSuliana Manley
doi: https://doi.org/10.1101/2021.10.04.463102
Dora Mahecic
1Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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  • For correspondence: suliana.manley@epfl.ch dora.mahecic@gmail.com
Willi L. Stepp
1Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Chen Zhang
1Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Juliette Griffié
1Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Martin Weigert
2Institute of Bioengineering, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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Suliana Manley
1Institute of Physics, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
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  • ORCID record for Suliana Manley
  • For correspondence: suliana.manley@epfl.ch dora.mahecic@gmail.com
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Abstract

In fluorescence microscopy, the amount of information that can be collected from the sample is limited, often due to constraints imposed by photobleaching and phototoxicity. Here, we report an event-driven acquisition (EDA) framework, which combines real-time, neural network-based recognition of events of interest with automated control of the imaging parameters in an instant structured illumination microscope (iSIM). On-the-fly prioritization of imaging rate or experiment duration is achieved by switching between a slow imaging rate to detect the onset of biological events of interest and a fast imaging rate to enable high information content during their progression. In this way, EDA allows the data capture of mitochondrial and bacterial divisions at imaging rates that match their dynamic timescales, while extending the accessible imaging duration, and thereby increases the density of relevant information in the acquired data.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 05, 2021.
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Event-driven acquisition for content-enriched microscopy
Dora Mahecic, Willi L. Stepp, Chen Zhang, Juliette Griffié, Martin Weigert, Suliana Manley
bioRxiv 2021.10.04.463102; doi: https://doi.org/10.1101/2021.10.04.463102
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Event-driven acquisition for content-enriched microscopy
Dora Mahecic, Willi L. Stepp, Chen Zhang, Juliette Griffié, Martin Weigert, Suliana Manley
bioRxiv 2021.10.04.463102; doi: https://doi.org/10.1101/2021.10.04.463102

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