Presentation
28 September 2023 Decoding microplankton life through holographic microscopy and deep learning
Author Affiliations +
Abstract
We demonstrate a new technique that combines holographic microscopy and deep learning to track microplankton through multiple generations, and measure their 3D positions and dry mass. The method is minimally invasive and non-destructive to the plankton cells, allowing us to study their trophic interactions, feeding events, and bio mass increase throughout the cell cycle. We evaluate the method on various plankton species belonging to different trophic levels, and observe the dry mass transfer during feeding interactions and diatom growth dynamics. Our approach provides a valuable tool for understanding microplankton behaviour and interactions in the oceanic food web.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harshith Bachimanchi, Benjamin Midtvedt, Daniel Midtvedt, Erik Selander, and Giovanni Volpe "Decoding microplankton life through holographic microscopy and deep learning", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550L (28 September 2023); https://doi.org/10.1117/12.2677603
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KEYWORDS
Deep learning

Holography

Microscopy

Carbon

Biomass

Environmental monitoring

Oceanography

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