Deep-Z: 3D virtual refocusing of fluorescence images using deep learning

Yichen Wu; Yair Rivenson; Hongda Wang; Yilin Luo; Eyal Ben-David; Laurent A. Bentolila; Christian Pritz; Aydogan Ozcan

doi:10.1364/CLEO_AT.2020.AW3T.6

Deep-Z: 3D virtual refocusing of fluorescence images using deep learning

Yichen Wu, Yair Rivenson, Hongda Wang, Yilin Luo, Eyal Ben-David, Laurent A. Bentolila, Christian Pritz, Aydogan Ozcan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We demonstrate a deep learning-based 3D virtual refocusing framework for fluorescence microscopy, which extends the imaging depth-of-field by 20-fold and corrects various aberrations, all digitally performed after a 2D image of the sample is captured.

Original language	English
Title of host publication	CLEO
Subtitle of host publication	Applications and Technology, CLEO_AT 2020
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580767
DOIs	https://doi.org/10.1364/CLEO_AT.2020.AW3T.6
State	Published - 2020
Externally published	Yes
Event	CLEO: Applications and Technology, CLEO_AT 2020 - Washington, United States Duration: 10 May 2020 → 15 May 2020

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F181-CLEO-AT 2020
ISSN (Electronic)	2162-2701

Conference

Conference	CLEO: Applications and Technology, CLEO_AT 2020
Country/Territory	United States
City	Washington
Period	10/05/20 → 15/05/20

Bibliographical note

Publisher Copyright:
CLEO 2020 © OSA 2020, © 2020 The Author(s).

Access to Document

10.1364/CLEO_AT.2020.AW3T.6

Cite this

Wu, Y., Rivenson, Y., Wang, H., Luo, Y., Ben-David, E., Bentolila, L. A., Pritz, C., & Ozcan, A. (2020). Deep-Z: 3D virtual refocusing of fluorescence images using deep learning. In CLEO: Applications and Technology, CLEO_AT 2020 Article AW3T.6 (Optics InfoBase Conference Papers; Vol. Part F181-CLEO-AT 2020). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/CLEO_AT.2020.AW3T.6

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title = "Deep-Z: 3D virtual refocusing of fluorescence images using deep learning",

abstract = "We demonstrate a deep learning-based 3D virtual refocusing framework for fluorescence microscopy, which extends the imaging depth-of-field by 20-fold and corrects various aberrations, all digitally performed after a 2D image of the sample is captured.",

author = "Yichen Wu and Yair Rivenson and Hongda Wang and Yilin Luo and Eyal Ben-David and Bentolila, {Laurent A.} and Christian Pritz and Aydogan Ozcan",

note = "Publisher Copyright: CLEO 2020 {\textcopyright} OSA 2020, {\textcopyright} 2020 The Author(s).; CLEO: Applications and Technology, CLEO_AT 2020 ; Conference date: 10-05-2020 Through 15-05-2020",

year = "2020",

doi = "10.1364/CLEO_AT.2020.AW3T.6",

language = "אנגלית",

isbn = "9781943580767",

series = "Optics InfoBase Conference Papers",

publisher = "Optica Publishing Group (formerly OSA)",

booktitle = "CLEO",

}

Wu, Y, Rivenson, Y, Wang, H, Luo, Y, Ben-David, E, Bentolila, LA, Pritz, C & Ozcan, A 2020, Deep-Z: 3D virtual refocusing of fluorescence images using deep learning. in CLEO: Applications and Technology, CLEO_AT 2020., AW3T.6, Optics InfoBase Conference Papers, vol. Part F181-CLEO-AT 2020, Optica Publishing Group (formerly OSA), CLEO: Applications and Technology, CLEO_AT 2020, Washington, United States, 10/05/20. https://doi.org/10.1364/CLEO_AT.2020.AW3T.6

Deep-Z: 3D virtual refocusing of fluorescence images using deep learning. / Wu, Yichen; Rivenson, Yair; Wang, Hongda et al.
CLEO: Applications and Technology, CLEO_AT 2020. Optica Publishing Group (formerly OSA), 2020. AW3T.6 (Optics InfoBase Conference Papers; Vol. Part F181-CLEO-AT 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Pritz, Christian

AU - Ozcan, Aydogan

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AB - We demonstrate a deep learning-based 3D virtual refocusing framework for fluorescence microscopy, which extends the imaging depth-of-field by 20-fold and corrects various aberrations, all digitally performed after a 2D image of the sample is captured.

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ER -

Deep-Z: 3D virtual refocusing of fluorescence images using deep learning

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