Deep-learning-enabled holographic polarization microscopy

Tairan Liu; Kevin de Haan; Bijie Bai; Yair Rivenson; Yi Luo; Hongda Wang; David Karalli; Hongxiang Fu; Yibo Zhang; John FitzGerald; Aydogan Ozcan

Deep-learning-enabled holographic polarization microscopy

Tairan Liu
, Kevin de Haan
, Bijie Bai
, Yair Rivenson
, Yi Luo
, Hongda Wang
, David Karalli
, Hongxiang Fu
, Yibo Zhang
, John FitzGerald
, Aydogan Ozcan

Research output: Contribution to journal › Conference article › peer-review

Abstract

We present a deep learning-based holographic polarization microscopy framework that can transform amplitude and phase information of samples into birefringence retardance and orientation images using holograms collected under a single polarization state.

Original language	English
Article number	ATh4F.5
Journal	Optics InfoBase Conference Papers
State	Published - 1 Jan 2021
Externally published	Yes
Event	CLEO: Applications and Technology, CLEO:A and T 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021 - Virtual, Online, United States Duration: 9 May 2021 → 14 May 2021

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

Cite this

@article{72e766bcbee4417bb5e78d751972c276,

title = "Deep-learning-enabled holographic polarization microscopy",

abstract = "We present a deep learning-based holographic polarization microscopy framework that can transform amplitude and phase information of samples into birefringence retardance and orientation images using holograms collected under a single polarization state.",

author = "Tairan Liu and \{de Haan\}, Kevin and Bijie Bai and Yair Rivenson and Yi Luo and Hongda Wang and David Karalli and Hongxiang Fu and Yibo Zhang and John FitzGerald and Aydogan Ozcan",

note = "Publisher Copyright: {\textcopyright} OSA 2021, {\textcopyright} 2021 The Author(s); CLEO: Applications and Technology, CLEO:A and T 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021 ; Conference date: 09-05-2021 Through 14-05-2021",

year = "2021",

month = jan,

day = "1",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

}

TY - JOUR

T1 - Deep-learning-enabled holographic polarization microscopy

AU - Liu, Tairan

AU - de Haan, Kevin

AU - Bai, Bijie

AU - Rivenson, Yair

AU - Luo, Yi

AU - Wang, Hongda

AU - Karalli, David

AU - Fu, Hongxiang

AU - Zhang, Yibo

AU - FitzGerald, John

AU - Ozcan, Aydogan

PY - 2021/1/1

Y1 - 2021/1/1

N2 - We present a deep learning-based holographic polarization microscopy framework that can transform amplitude and phase information of samples into birefringence retardance and orientation images using holograms collected under a single polarization state.

AB - We present a deep learning-based holographic polarization microscopy framework that can transform amplitude and phase information of samples into birefringence retardance and orientation images using holograms collected under a single polarization state.

UR - https://www.scopus.com/pages/publications/85119531466

M3 - Conference article

AN - SCOPUS:85119531466

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - ATh4F.5

T2 - CLEO: Applications and Technology, CLEO:A and T 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021

Y2 - 9 May 2021 through 14 May 2021

ER -

Deep-learning-enabled holographic polarization microscopy

Abstract

ASJC Scopus subject areas

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