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5 March 2021 Label-free detection of Giardia lamblia cysts in water samples using a field-portable imaging flow cytometer and deep learning
Zoltán S. Göröcs, David Baum, Fang Song, Kevin De Haan, Hatice Ceylan Koydemir, Yunzhe Qiu, Zilin Cai, Thamira Skandakumar, Spencer Peterman, Miu Tamamitsu, Aydogan Ozcan
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Proceedings Volume 11632, Optics and Biophotonics in Low-Resource Settings VII; 116320G (2021) https://doi.org/10.1117/12.2579482
Event: SPIE BiOS, 2021, Online Only
Abstract
We report a label-free, field-portable, holographic imaging flow cytometer that can automatically detect and count Giardia lamblia cysts in water samples with a throughput of 100 mL/h. Our cytometer has the dimensions of 19×19×16 cm and a laptop computer-connected to it reconstructs the phase and intensity images of the flowing microparticles in the sample at three different wavelengths and classifies them by a trained convolutional neural network, thereby detecting the Giardia cysts in real time. We experimentally demonstrated that our system can detect Giardia contamination in fresh and seawater samples containing as low as <10 cysts/50 mL.
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Zoltán S. Göröcs, David Baum, Fang Song, Kevin De Haan, Hatice Ceylan Koydemir, Yunzhe Qiu, Zilin Cai, Thamira Skandakumar, Spencer Peterman, Miu Tamamitsu, and Aydogan Ozcan "Label-free detection of Giardia lamblia cysts in water samples using a field-portable imaging flow cytometer and deep learning", Proc. SPIE 11632, Optics and Biophotonics in Low-Resource Settings VII, 116320G (5 March 2021); https://doi.org/10.1117/12.2579482
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KEYWORDS
Water
Chlorine
Computational imaging
Contamination
Convolutional neural networks
Holograms
Holography
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