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Journal article 574 views 78 downloads

Diagnostic Potential of Imaging Flow Cytometry

Minh Doan, Ivan Vorobjev, Paul Rees Orcid Logo, Andrew Filby, Olaf Wolkenhauer, Anne E. Goldfeld, Judy Lieberman, Natasha Barteneva, Anne E. Carpenter, Holger Hennig

Trends in Biotechnology

Swansea University Author: Paul Rees Orcid Logo

Abstract

Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of single cells within minutes. IFC is seeing a paradigm shift from low- to high-information-content analysis, driven partly by deep learning algorithms. We predict a wealth of applications with potential translation...

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Published in: Trends in Biotechnology
ISSN: 0167-7799
Published: 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa38407
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Abstract: Imaging flow cytometry (IFC) captures multichannel images of hundreds of thousands of single cells within minutes. IFC is seeing a paradigm shift from low- to high-information-content analysis, driven partly by deep learning algorithms. We predict a wealth of applications with potential translation into clinical practice.
Keywords: deep learning; disease diagnostics; high-content analysis; imaging flow cytometry; translational medicine
College: College of Engineering