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30 May 2022 From phase imaging to CNN-based quantitative representation
Cédric P. Allier, Lionel Hervé, Chiara Paviolo, Ondrej Mandula, Olivier Cioni, William Pierré, Kiran Padmanabhan, Francesca Andriani, Sophie Morales
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Proceedings Volume PC12136, Unconventional Optical Imaging III; PC121360T (2022) https://doi.org/10.1117/12.2625595
Event: SPIE Photonics Europe, 2022, Strasbourg, France
Abstract
We present a CNN-based quantification pipeline for the imaging and analysis of adherent cell cultures. The imaging part features two CNNs dedicated to lens-free microscopy performing accelerated holographic reconstruction and phase unwrapping. The analysis part features CNNs estimating several cellular metrics. These CNNs maps phase image into 2D quantitative representations of cell positions and measurements. The outputs images are processed by a local maxima algorithm to obtain a list of cell measurements. Here, we discuss the performance and limitations of this CNN-based quantification pipeline. The advantage is the fast processing time, i.e. the analysis of ~10.000 cells in 10 seconds.
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Cédric P. Allier, Lionel Hervé, Chiara Paviolo, Ondrej Mandula, Olivier Cioni, William Pierré, Kiran Padmanabhan, Francesca Andriani, and Sophie Morales "From phase imaging to CNN-based quantitative representation", Proc. SPIE PC12136, Unconventional Optical Imaging III, PC121360T (30 May 2022); https://doi.org/10.1117/12.2625595
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KEYWORDS
Phase imaging
Microscopy
3D image reconstruction
Holography
Live cell imaging
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