Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer
Author:
Affiliation:
1. Electrical and Computer Engineering Department
2. University of California, Los Angeles
3. Los Angeles
4. USA
5. Bioengineering Department
Abstract
We developed a field-portable and cost-effective imaging flow cytometer that uses deep learning to accurately detect Giardia cysts in water samples.
Funder
Army Research Office
Publisher
Royal Society of Chemistry (RSC)
Subject
Biomedical Engineering,General Chemistry,Biochemistry,Bioengineering
Link
http://pubs.rsc.org/en/content/articlepdf/2020/LC/D0LC00708K
Reference29 articles.
1. Five facts about Giardia lamblia
2. US EPA, Surface Water Treatment Rules, https://www.epa.gov/dwreginfo/surface-water-treatment-rules
3. Evolution of monitoring for Giardia and Cryptosporidium in water
4. Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning
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