Journal article 832 views 153 downloads
Diagnostic Potential of Imaging Flow Cytometry
Minh Doan,
Ivan Vorobjev,
Paul Rees 
,
Andrew Filby,
Olaf Wolkenhauer,
Anne E. Goldfeld,
Judy Lieberman,
Natasha Barteneva,
Anne E. Carpenter,
Holger Hennig
,
Andrew Filby,
Olaf Wolkenhauer,
Anne E. Goldfeld,
Judy Lieberman,
Natasha Barteneva,
Anne E. Carpenter,
Holger Hennig
Trends in Biotechnology
Swansea University Author:
Paul Rees
-
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DOI (Published version): 10.1016/j.tibtech.2017.12.008
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...
| Published in: | Trends in Biotechnology |
|---|---|
| ISSN: | 0167-7799 |
| Published: |
2018
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| Online Access: |
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| 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: |
Faculty of Science and Engineering |