Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks

Yair Rivenson; Zoltán Göröcs; Harun Günaydin; Yibo Zhang; Hongda Wang; Aydogan Ozcan

doi:10.1364/CLEO_AT.2018.AM1J.5

Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks

Yair Rivenson
, Zoltán Göröcs
, Harun Günaydin
, Yibo Zhang
, Hongda Wang
, Aydogan Ozcan

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

2 Scopus citations

Abstract

We demonstrate the ability of deep convolutional neural networks to significantly enhance the spatial resolution, field-of-view and depth-of-field of optical microscopy images, without any hardware modification to the imaging system.

Original language	English
Title of host publication	CLEO
Subtitle of host publication	Applications and Technology, CLEO_AT 2018
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580422
DOIs	https://doi.org/10.1364/CLEO_AT.2018.AM1J.5
State	Published - 1 Jan 2018
Externally published	Yes
Event	CLEO: Applications and Technology, CLEO_AT 2018 - San Jose, United States Duration: 13 May 2018 → 18 May 2018

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F92-CLEO_AT 2018
ISSN (Electronic)	2162-2701

Conference

Conference	CLEO: Applications and Technology, CLEO_AT 2018
Country/Territory	United States
City	San Jose
Period	13/05/18 → 18/05/18

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Access to Document

10.1364/CLEO_AT.2018.AM1J.5

Cite this

Rivenson, Y., Göröcs, Z., Günaydin, H., Zhang, Y., Wang, H., & Ozcan, A. (2018). Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks. In CLEO: Applications and Technology, CLEO_AT 2018 (Optics InfoBase Conference Papers; Vol. Part F92-CLEO_AT 2018). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/CLEO_AT.2018.AM1J.5

@inproceedings{a0fc08cef4cc49f5bd525197a906870a,

title = "Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks",

abstract = "We demonstrate the ability of deep convolutional neural networks to significantly enhance the spatial resolution, field-of-view and depth-of-field of optical microscopy images, without any hardware modification to the imaging system.",

author = "Yair Rivenson and Zolt{\'a}n G{\"o}r{\"o}cs and Harun G{\"u}naydin and Yibo Zhang and Hongda Wang and Aydogan Ozcan",

note = "Publisher Copyright: {\textcopyright} OSA 2018.; CLEO: Applications and Technology, CLEO\_AT 2018 ; Conference date: 13-05-2018 Through 18-05-2018",

year = "2018",

month = jan,

day = "1",

doi = "10.1364/CLEO\_AT.2018.AM1J.5",

language = "English",

isbn = "9781943580422",

series = "Optics InfoBase Conference Papers",

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

booktitle = "CLEO",

}

Rivenson, Y, Göröcs, Z, Günaydin, H, Zhang, Y, Wang, H & Ozcan, A 2018, Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks. in CLEO: Applications and Technology, CLEO_AT 2018. Optics InfoBase Conference Papers, vol. Part F92-CLEO_AT 2018, Optica Publishing Group (formerly OSA), CLEO: Applications and Technology, CLEO_AT 2018, San Jose, United States, 13/05/18. https://doi.org/10.1364/CLEO_AT.2018.AM1J.5

Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks. / Rivenson, Yair; Göröcs, Zoltán; Günaydin, Harun et al.
CLEO: Applications and Technology, CLEO_AT 2018. Optica Publishing Group (formerly OSA), 2018. (Optics InfoBase Conference Papers; Vol. Part F92-CLEO_AT 2018).

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

TY - GEN

T1 - Deep learning microscopy

T2 - CLEO: Applications and Technology, CLEO_AT 2018

AU - Rivenson, Yair

AU - Göröcs, Zoltán

AU - Günaydin, Harun

AU - Zhang, Yibo

AU - Wang, Hongda

AU - Ozcan, Aydogan

PY - 2018/1/1

Y1 - 2018/1/1

N2 - We demonstrate the ability of deep convolutional neural networks to significantly enhance the spatial resolution, field-of-view and depth-of-field of optical microscopy images, without any hardware modification to the imaging system.

AB - We demonstrate the ability of deep convolutional neural networks to significantly enhance the spatial resolution, field-of-view and depth-of-field of optical microscopy images, without any hardware modification to the imaging system.

UR - https://www.scopus.com/pages/publications/85049149891

U2 - 10.1364/CLEO_AT.2018.AM1J.5

DO - 10.1364/CLEO_AT.2018.AM1J.5

M3 - Conference contribution

AN - SCOPUS:85049149891

SN - 9781943580422

T3 - Optics InfoBase Conference Papers

BT - CLEO

PB - Optica Publishing Group (formerly OSA)

Y2 - 13 May 2018 through 18 May 2018

ER -

Deep learning microscopy: Enhancing resolution, field-of- view and depth-of-field of optical microscopy images using neural networks

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

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