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Deep learning-based virtual staining of unlabeled tissue samples

  • Kevin de Haan
  • , Yair Rivenson
  • , Zhensong Wei
  • , Hongda Wang
  • , Tairan Liu
  • , W. Dean Wallace
  • , Aydogan Ozcan

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

Abstract

We present a deep learning-based framework to perform virtual histological staining of label-free tissue samples. This framework is effective for various tissue-stain combinations using autofluorescence or quantitative phase images as input to trained neural networks.

Original languageEnglish
Title of host publicationMicroscopy Histopathology and Analytics, Microscopy 2020
PublisherOptica Publishing Group (formerly OSA)
ISBN (Print)9781943580743
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes
EventMicroscopy Histopathology and Analytics, Microscopy 2020 - Washington, United States
Duration: 20 Apr 202023 Apr 2020

Publication series

NameOptics InfoBase Conference Papers
VolumePart F177-Microscopy-2020
ISSN (Electronic)2162-2701

Conference

ConferenceMicroscopy Histopathology and Analytics, Microscopy 2020
Country/TerritoryUnited States
City Washington
Period20/04/2023/04/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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