Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning

Yilin Luo; Yichen Wu; Gunvant Chaudhari; Yair Rivenson; Ayfer Calis; Kevin De Haan; Aydogan Ozcan

doi:10.1364/CLEO_AT.2019.AM2I.3

Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning

Yilin Luo, Yichen Wu, Gunvant Chaudhari, Yair Rivenson, Ayfer Calis, Kevin De Haan, Aydogan Ozcan

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

Abstract

Deep learning-based holographic reconstruction method eliminates twin-image, speckle and other interference artifacts at the output image, matching the contrast of bright-field microscopy, and merges volumetric imaging capability of holography with the contrast of incoherent microscopy.

Original language	English
Title of host publication	CLEO
Subtitle of host publication	Applications and Technology, CLEO_AT 2019
Publisher	Optica Publishing Group (formerly OSA)
ISBN (Print)	9781943580576
DOIs	https://doi.org/10.1364/CLEO_AT.2019.AM2I.3
State	Published - 1 Jan 2019
Externally published	Yes
Event	CLEO: Applications and Technology, CLEO_AT 2019 - San Jose, United States Duration: 5 May 2019 → 10 May 2019

Publication series

Name	Optics InfoBase Conference Papers
Volume	Part F127-CLEO_AT 2019
ISSN (Electronic)	2162-2701

Conference

Conference	CLEO: Applications and Technology, CLEO_AT 2019
Country/Territory	United States
City	San Jose
Period	5/05/19 → 10/05/19

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Access to Document

10.1364/CLEO_AT.2019.AM2I.3

Cite this

Luo, Y., Wu, Y., Chaudhari, G., Rivenson, Y., Calis, A., De Haan, K., & Ozcan, A. (2019). Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning. In CLEO: Applications and Technology, CLEO_AT 2019 (Optics InfoBase Conference Papers; Vol. Part F127-CLEO_AT 2019). Optica Publishing Group (formerly OSA). https://doi.org/10.1364/CLEO_AT.2019.AM2I.3

@inproceedings{94ed1c4970e3413f9927586994ee4840,

title = "Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning",

abstract = "Deep learning-based holographic reconstruction method eliminates twin-image, speckle and other interference artifacts at the output image, matching the contrast of bright-field microscopy, and merges volumetric imaging capability of holography with the contrast of incoherent microscopy.",

author = "Yilin Luo and Yichen Wu and Gunvant Chaudhari and Yair Rivenson and Ayfer Calis and \{De Haan\}, Kevin and Aydogan Ozcan",

note = "Publisher Copyright: {\textcopyright} 2019 The Author(s); CLEO: Applications and Technology, CLEO\_AT 2019 ; Conference date: 05-05-2019 Through 10-05-2019",

year = "2019",

month = jan,

day = "1",

doi = "10.1364/CLEO\_AT.2019.AM2I.3",

language = "English",

isbn = "9781943580576",

series = "Optics InfoBase Conference Papers",

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

booktitle = "CLEO",

}

Luo, Y, Wu, Y, Chaudhari, G, Rivenson, Y, Calis, A, De Haan, K & Ozcan, A 2019, Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning. in CLEO: Applications and Technology, CLEO_AT 2019. Optics InfoBase Conference Papers, vol. Part F127-CLEO_AT 2019, Optica Publishing Group (formerly OSA), CLEO: Applications and Technology, CLEO_AT 2019, San Jose, United States, 5/05/19. https://doi.org/10.1364/CLEO_AT.2019.AM2I.3

Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning. / Luo, Yilin; Wu, Yichen; Chaudhari, Gunvant et al.
CLEO: Applications and Technology, CLEO_AT 2019. Optica Publishing Group (formerly OSA), 2019. (Optics InfoBase Conference Papers; Vol. Part F127-CLEO_AT 2019).

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

TY - GEN

T1 - Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning

AU - Luo, Yilin

AU - Wu, Yichen

AU - Chaudhari, Gunvant

AU - Rivenson, Yair

AU - Calis, Ayfer

AU - De Haan, Kevin

AU - Ozcan, Aydogan

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Deep learning-based holographic reconstruction method eliminates twin-image, speckle and other interference artifacts at the output image, matching the contrast of bright-field microscopy, and merges volumetric imaging capability of holography with the contrast of incoherent microscopy.

AB - Deep learning-based holographic reconstruction method eliminates twin-image, speckle and other interference artifacts at the output image, matching the contrast of bright-field microscopy, and merges volumetric imaging capability of holography with the contrast of incoherent microscopy.

UR - https://www.scopus.com/pages/publications/85068192693

U2 - 10.1364/CLEO_AT.2019.AM2I.3

DO - 10.1364/CLEO_AT.2019.AM2I.3

M3 - Conference contribution

AN - SCOPUS:85068192693

SN - 9781943580576

T3 - Optics InfoBase Conference Papers

BT - CLEO

PB - Optica Publishing Group (formerly OSA)

T2 - CLEO: Applications and Technology, CLEO_AT 2019

Y2 - 5 May 2019 through 10 May 2019

ER -

Holographic reconstruction with bright-field microscopy contrast using cross-modality deep learning

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

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