Neural network-based single-shot autofocusing of microscopy images

Luzhe Huang; Yilin Luo; Yair Rivenson; Aydogan Ozcan

Neural network-based single-shot autofocusing of microscopy images

Luzhe Huang, Yilin Luo, Yair Rivenson, Aydogan Ozcan

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

Abstract

Using fluorescence and brightfield microscopy modalities, we demonstrate a deep learning-based offline autofocusing method to blindly autofocus an image that is captured at an unknown out-of-focus distance or on a tilted sample plane.

Original language	English
Article number	ATu4L.2
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{e22c12163b854e148827e805511fba77,

title = "Neural network-based single-shot autofocusing of microscopy images",

abstract = "Using fluorescence and brightfield microscopy modalities, we demonstrate a deep learning-based offline autofocusing method to blindly autofocus an image that is captured at an unknown out-of-focus distance or on a tilted sample plane.",

author = "Luzhe Huang and Yilin Luo and Yair Rivenson 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 - Neural network-based single-shot autofocusing of microscopy images

AU - Huang, Luzhe

AU - Luo, Yilin

AU - Rivenson, Yair

AU - Ozcan, Aydogan

PY - 2021/1/1

Y1 - 2021/1/1

N2 - Using fluorescence and brightfield microscopy modalities, we demonstrate a deep learning-based offline autofocusing method to blindly autofocus an image that is captured at an unknown out-of-focus distance or on a tilted sample plane.

AB - Using fluorescence and brightfield microscopy modalities, we demonstrate a deep learning-based offline autofocusing method to blindly autofocus an image that is captured at an unknown out-of-focus distance or on a tilted sample plane.

UR - https://www.scopus.com/pages/publications/85119485770

M3 - Conference article

AN - SCOPUS:85119485770

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - ATu4L.2

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 -

Neural network-based single-shot autofocusing of microscopy images

Abstract

ASJC Scopus subject areas

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