Literature DB >> 32341878

Label-free imaging flow cytometer for analyzing large cell populations by line-field quantitative phase microscopy with digital refocusing.

Hidenao Yamada1, Amane Hirotsu2, Daisuke Yamashita1, Osamu Yasuhiko1, Toyohiko Yamauchi1, Tsukasa Kayou3, Hiroaki Suzuki3, Shigetoshi Okazaki4, Hirotoshi Kikuchi2, Hiroya Takeuchi2, Yukio Ueda1.   

Abstract

We propose a line-field quantitative phase-imaging flow cytometer for analyzing large populations of label-free cells. Hydrodynamical focusing brings cells into the focus plane of an optical system while diluting the cell suspension, resulting in decreased throughput rate. To overcome the trade-off between throughput rate and in-focus imaging, our cytometer involves digitally extending the depth-of-focus on loosely hydrodynamically focusing cell suspensions. The cells outside the depth-of-focus range in the 70-µm diameter of the core flow were automatically digitally refocused after image acquisition. We verified that refocusing was successful with our cytometer through statistical analysis of image quality before and after digital refocusing.
© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.

Year:  2020        PMID: 32341878      PMCID: PMC7173910          DOI: 10.1364/BOE.389435

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  32 in total

1.  Focus plane detection criteria in digital holography microscopy by amplitude analysis.

Authors:  Frank Dubois; Cédric Schockaert; Natcaha Callens; Catherine Yourassowsky
Journal:  Opt Express       Date:  2006-06-26       Impact factor: 3.894

2.  Influence of defocus on quantitative analysis of microscopic objects and individual cells with digital holography.

Authors:  Matthew T Rinehart; Han Sang Park; Adam Wax
Journal:  Biomed Opt Express       Date:  2015-05-11       Impact factor: 3.732

3.  Intelligent Image-Activated Cell Sorting.

Authors:  Nao Nitta; Takeaki Sugimura; Akihiro Isozaki; Hideharu Mikami; Kei Hiraki; Shinya Sakuma; Takanori Iino; Fumihito Arai; Taichiro Endo; Yasuhiro Fujiwaki; Hideya Fukuzawa; Misa Hase; Takeshi Hayakawa; Kotaro Hiramatsu; Yu Hoshino; Mary Inaba; Takuro Ito; Hiroshi Karakawa; Yusuke Kasai; Kenichi Koizumi; SangWook Lee; Cheng Lei; Ming Li; Takanori Maeno; Satoshi Matsusaka; Daichi Murakami; Atsuhiro Nakagawa; Yusuke Oguchi; Minoru Oikawa; Tadataka Ota; Kiyotaka Shiba; Hirofumi Shintaku; Yoshitaka Shirasaki; Kanako Suga; Yuta Suzuki; Nobutake Suzuki; Yo Tanaka; Hiroshi Tezuka; Chihana Toyokawa; Yaxiaer Yalikun; Makoto Yamada; Mai Yamagishi; Takashi Yamano; Atsushi Yasumoto; Yutaka Yatomi; Masayuki Yazawa; Dino Di Carlo; Yoichiroh Hosokawa; Sotaro Uemura; Yasuyuki Ozeki; Keisuke Goda
Journal:  Cell       Date:  2018-08-27       Impact factor: 41.582

4.  Edge sparsity criterion for robust holographic autofocusing.

Authors:  Yibo Zhang; Hongda Wang; Yichen Wu; Miu Tamamitsu; Aydogan Ozcan
Journal:  Opt Lett       Date:  2017-10-01       Impact factor: 3.776

5.  Invited Article: Digital refocusing in quantitative phase imaging for flowing red blood cells.

Authors:  Han Sang Park; Silvia Ceballos; Will J Eldridge; Adam Wax
Journal:  APL Photonics       Date:  2018-10-02

6.  High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

Authors:  Baoshan Guo; Cheng Lei; Hirofumi Kobayashi; Takuro Ito; Yaxiaer Yalikun; Yiyue Jiang; Yo Tanaka; Yasuyuki Ozeki; Keisuke Goda
Journal:  Cytometry A       Date:  2017-04-11       Impact factor: 4.355

7.  Label-free classification of cells based on supervised machine learning of subcellular structures.

Authors:  Yusuke Ozaki; Hidenao Yamada; Hirotoshi Kikuchi; Amane Hirotsu; Tomohiro Murakami; Tomohiro Matsumoto; Toshiki Kawabata; Yoshihiro Hiramatsu; Kinji Kamiya; Toyohiko Yamauchi; Kentaro Goto; Yukio Ueda; Shigetoshi Okazaki; Masatoshi Kitagawa; Hiroya Takeuchi; Hiroyuki Konno
Journal:  PLoS One       Date:  2019-01-29       Impact factor: 3.240

8.  Deep Learning in Label-free Cell Classification.

Authors:  Claire Lifan Chen; Ata Mahjoubfar; Li-Chia Tai; Ian K Blaby; Allen Huang; Kayvan Reza Niazi; Bahram Jalali
Journal:  Sci Rep       Date:  2016-03-15       Impact factor: 4.379

9.  Label-free cell cycle analysis for high-throughput imaging flow cytometry.

Authors:  Thomas Blasi; Holger Hennig; Huw D Summers; Fabian J Theis; Joana Cerveira; James O Patterson; Derek Davies; Andrew Filby; Anne E Carpenter; Paul Rees
Journal:  Nat Commun       Date:  2016-01-07       Impact factor: 14.919

10.  Tomographic flow cytometry by digital holography.

Authors:  Francesco Merola; Pasquale Memmolo; Lisa Miccio; Roberto Savoia; Martina Mugnano; Angelo Fontana; Giuliana D'Ippolito; Angela Sardo; Achille Iolascon; Antonella Gambale; Pietro Ferraro
Journal:  Light Sci Appl       Date:  2017-04-07       Impact factor: 17.782

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  1 in total

1.  Developing a Reliable Holographic Flow Cyto-Tomography Apparatus by Optimizing the Experimental Layout and Computational Processing.

Authors:  Jaromír Běhal; Francesca Borrelli; Martina Mugnano; Vittorio Bianco; Amedeo Capozzoli; Claudio Curcio; Angelo Liseno; Lisa Miccio; Pasquale Memmolo; Pietro Ferraro
Journal:  Cells       Date:  2022-08-19       Impact factor: 7.666

  1 in total

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