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Conference Paper: Ultrafast quantitative time-stretch imaging flow cytometry of phytoplankton

TitleUltrafast quantitative time-stretch imaging flow cytometry of phytoplankton
Authors
Issue Date2016
PublisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml?WT.svl=mddp2
Citation
The 2016 SPIE Photonics West Conference, San Francisco, CA., 13-18 February 2016. In Conference Proceedings, 2016, v. 9720, paper no. 9720-35 How to Cite?
AbstractComprehensive quantification of phytoplankton abundance, sizes and other parameters, e.g. biomasses, has been an important, yet daunting task in aquatic sciences and biofuel research. It is primarily because of the lack of effective tool to image and thus accurately profile individual microalgae in a large population. The phytoplankton species are highly diversified and heterogeneous in terms of their sizes and the richness in morphological complexity. This fact makes time-stretch imaging, a new ultrafast real-time optical imaging technology, particularly suitable for ultralarge-scale taxonomic classification of phytoplankton together with quantitative image recognition and analysis. We here demonstrate quantitative imaging flow cytometry of single phytoplankton based on quantitative asymmetric-detection time-stretch optical microscopy (Q-ATOM) – a new time-stretch imaging modality for label-free quantitative phase imaging without interferometric implementations. Sharing the similar concept of Schlieren imaging, Q-ATOM accesses multiple phase-gradient contrasts of each single phytoplankton, from which the quantitative phase profile is computed. We employ such system to capture, at an imaging line-scan rate of 11.6 MHz, high-resolution images of two phytoplankton populations (scenedesmus and chlamydomonas) in ultrafast microfluidic flow (3 m/s). We further perform quantitative taxonomic screening analysis enabled by this technique. More importantly, the system can also generate quantitative phase images of single phytoplankton. This is especially useful for label-free quantification of biomasses (e.g. lipid droplets) of the particular species of interest – an important task adopted in biofuel applications. Combining machine learning for automated classification, Q-ATOM could be an attractive platform for continuous and real-time ultralarge-scale single-phytoplankton analysis.
DescriptionBiomedical Spectroscopy, Microscopy, and Imaging: 9720 - High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management: Paper 9720-35
Persistent Identifierhttp://hdl.handle.net/10722/234153
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLai, QTK-
dc.contributor.authorLau, AKS-
dc.contributor.authorTang, AHL-
dc.contributor.authorWong, KKY-
dc.contributor.authorTsia, KKM-
dc.date.accessioned2016-10-14T06:59:24Z-
dc.date.available2016-10-14T06:59:24Z-
dc.date.issued2016-
dc.identifier.citationThe 2016 SPIE Photonics West Conference, San Francisco, CA., 13-18 February 2016. In Conference Proceedings, 2016, v. 9720, paper no. 9720-35-
dc.identifier.issn0277-786X-
dc.identifier.urihttp://hdl.handle.net/10722/234153-
dc.descriptionBiomedical Spectroscopy, Microscopy, and Imaging: 9720 - High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management: Paper 9720-35-
dc.description.abstractComprehensive quantification of phytoplankton abundance, sizes and other parameters, e.g. biomasses, has been an important, yet daunting task in aquatic sciences and biofuel research. It is primarily because of the lack of effective tool to image and thus accurately profile individual microalgae in a large population. The phytoplankton species are highly diversified and heterogeneous in terms of their sizes and the richness in morphological complexity. This fact makes time-stretch imaging, a new ultrafast real-time optical imaging technology, particularly suitable for ultralarge-scale taxonomic classification of phytoplankton together with quantitative image recognition and analysis. We here demonstrate quantitative imaging flow cytometry of single phytoplankton based on quantitative asymmetric-detection time-stretch optical microscopy (Q-ATOM) – a new time-stretch imaging modality for label-free quantitative phase imaging without interferometric implementations. Sharing the similar concept of Schlieren imaging, Q-ATOM accesses multiple phase-gradient contrasts of each single phytoplankton, from which the quantitative phase profile is computed. We employ such system to capture, at an imaging line-scan rate of 11.6 MHz, high-resolution images of two phytoplankton populations (scenedesmus and chlamydomonas) in ultrafast microfluidic flow (3 m/s). We further perform quantitative taxonomic screening analysis enabled by this technique. More importantly, the system can also generate quantitative phase images of single phytoplankton. This is especially useful for label-free quantification of biomasses (e.g. lipid droplets) of the particular species of interest – an important task adopted in biofuel applications. Combining machine learning for automated classification, Q-ATOM could be an attractive platform for continuous and real-time ultralarge-scale single-phytoplankton analysis.-
dc.languageeng-
dc.publisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml?WT.svl=mddp2-
dc.relation.ispartofSPIE - International Society for Optical Engineering Proceedings-
dc.rightsSPIE - International Society for Optical Engineering Proceedings. Copyright © SPIE - International Society for Optical Engineering.-
dc.titleUltrafast quantitative time-stretch imaging flow cytometry of phytoplankton-
dc.typeConference_Paper-
dc.identifier.emailLau, AKS: andylks@hku.hk-
dc.identifier.emailWong, KKY: kywong@eee.hku.hk-
dc.identifier.emailTsia, KKM: tsia@hku.hk-
dc.identifier.authorityWong, KKY=rp00189-
dc.identifier.authorityTsia, KKM=rp01389-
dc.identifier.doi10.1117/12.2212246-
dc.identifier.hkuros267556-
dc.identifier.volume9720, paper no. 9720-35-
dc.publisher.placeUnited States-
dc.description.otherThe 2016 SPIE Photonics West Conference, San Francisco, CA., 13-18 February 2016. In Conference Proceedings, 2016, v. 9720, paper no. 9720-35-

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