Presentation
4 October 2022 Quantitative microplankton tracking by holographic microscopy and deep learning (Conference Presentation)
Author Affiliations +
Abstract
We present a technique to track microplanktons through generations, and continuously measure their three-dimensional position and dry mass. By combining holographic microscopy with deep learning, the technique is minimally invasive and non-destructive for plankton cells, allowing quantitative assessments of trophic interactions such as feeding events, biomass increase throughout the cell cycle. We evaluate the performance of the method, by applying it to various plankton species belonging to different trophic levels. Finally, we demonstrate the dry mass transfer from cell to cell in prey-predator interactions, and show the growth dynamics from division to division in diatoms.
Conference Presentation
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Harshith Bachimanchi, Benjamin Midtvedt, Daniel Midtvedt, Erik Selander, and Giovanni Volpe "Quantitative microplankton tracking by holographic microscopy and deep learning (Conference Presentation)", Proc. SPIE PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040T (4 October 2022); https://doi.org/10.1117/12.2633790
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KEYWORDS
Holography

Microscopy

Carbon

3D metrology

Data processing

Oceanography

Time metrology

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