Volumetric fluorescence microscopy using convolutional recurrent neural networks

  • Luzhe Huang
  • , Yilin Luo
  • , Yair Rivenson
  • , Aydogan Ozcan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We demonstrate a convolutional recurrent neural network-based volumetric imaging framework, termed Recurrent-MZ. Using a few 2D fluorescence microscopy images as its input, Recurrent-MZ provides a 50-fold extended depth-of-field in imaging of 3D fluorescent samples.

Original languageEnglish
Title of host publication2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781943580910
StatePublished - 1 May 2021
Externally publishedYes
Event2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Virtual, Online, United States
Duration: 9 May 202114 May 2021

Publication series

Name2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Proceedings

Conference

Conference2021 Conference on Lasers and Electro-Optics, CLEO 2021
Country/TerritoryUnited States
CityVirtual, Online
Period9/05/2114/05/21

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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