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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
Keywordsasymmetric detection
imaging flow cytometry
optical time-stretch
phytoplankton
quantitative phase imaging
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 Proceedings of SPIE, 2016, v. 9720, article no. 972011 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
2023 SCImago Journal Rankings: 0.152
ISI Accession Number ID

 

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 Proceedings of SPIE, 2016, v. 9720, article no. 972011-
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.ispartofProceedings of SPIE-
dc.rightsCopyright 2016 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/12.2212246-
dc.subjectasymmetric detection-
dc.subjectimaging flow cytometry-
dc.subjectoptical time-stretch-
dc.subjectphytoplankton-
dc.subjectquantitative phase imaging-
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.description.naturepublished_or_final_version-
dc.identifier.doi10.1117/12.2212246-
dc.identifier.scopuseid_2-s2.0-84982084185-
dc.identifier.hkuros267556-
dc.identifier.volume9720-
dc.identifier.spagearticle no. 972011-
dc.identifier.epagearticle no. 972011-
dc.identifier.isiWOS:000383735900028-
dc.publisher.placeUnited States-
dc.identifier.issnl0277-786X-

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