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 proceedingConference contributionpeer-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 languageAmerican English
Title of host publicationCLEO
Subtitle of host publicationApplications and Technology, CLEO_AT 2020
PublisherOptica Publishing Group (formerly OSA)
ISBN (Print)9781943580767
DOIs
StatePublished - 2020
Externally publishedYes
EventCLEO: Applications and Technology, CLEO_AT 2020 - Washington, United States
Duration: 10 May 202015 May 2020

Publication series

NameOptics InfoBase Conference Papers
VolumePart F181-CLEO-AT 2020
ISSN (Electronic)2162-2701

Conference

ConferenceCLEO: Applications and Technology, CLEO_AT 2020
Country/TerritoryUnited States
CityWashington
Period10/05/2015/05/20

Bibliographical note

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

Fingerprint

Dive into the research topics of 'Deep-Z: 3D virtual refocusing of fluorescence images using deep learning'. Together they form a unique fingerprint.

Cite this