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

doi:10.1016/j.tibtech.2017.12.008

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

Research output: Contribution to journal › Short survey › peer-review

110 Scopus citations

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.

Original language	English (US)
Pages (from-to)	649-652
Number of pages	4
Journal	Trends in Biotechnology
Volume	36
Issue number	7
DOIs	https://doi.org/10.1016/j.tibtech.2017.12.008
State	Published - Jul 2018

Keywords

deep learning
disease diagnostics
high-content analysis
imaging flow cytometry
translational medicine

ASJC Scopus subject areas

Biotechnology
Bioengineering

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10.1016/j.tibtech.2017.12.008

Cite this

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title = "Diagnostic Potential of Imaging Flow Cytometry",

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",

author = "Minh Doan and Ivan Vorobjev and Paul Rees and Andrew Filby and Olaf Wolkenhauer and Goldfeld, {Anne E.} and Judy Lieberman and Natasha Barteneva and Carpenter, {Anne E.} and Holger Hennig",

note = "Publisher Copyright: {\textcopyright} 2018 The Authors",

year = "2018",

month = jul,

doi = "10.1016/j.tibtech.2017.12.008",

language = "English (US)",

volume = "36",

pages = "649--652",

journal = "Trends in Biotechnology",

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T1 - Diagnostic Potential of Imaging Flow Cytometry

AU - Doan, Minh

AU - Vorobjev, Ivan

AU - Rees, Paul

AU - Filby, Andrew

AU - Wolkenhauer, Olaf

AU - Goldfeld, Anne E.

AU - Lieberman, Judy

AU - Barteneva, Natasha

AU - Carpenter, Anne E.

AU - Hennig, Holger

PY - 2018/7

Y1 - 2018/7

N2 - 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.

AB - 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.

KW - deep learning

KW - disease diagnostics

KW - high-content analysis

KW - imaging flow cytometry

KW - translational medicine

UR - http://www.scopus.com/inward/record.url?scp=85041216958&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041216958&partnerID=8YFLogxK

U2 - 10.1016/j.tibtech.2017.12.008

DO - 10.1016/j.tibtech.2017.12.008

M3 - Short survey

C2 - 29395345

AN - SCOPUS:85041216958

SN - 0167-7799

VL - 36

SP - 649

EP - 652

JO - Trends in Biotechnology

JF - Trends in Biotechnology

IS - 7

ER -

Diagnostic Potential of Imaging Flow Cytometry

Abstract

Keywords

ASJC Scopus subject areas

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