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Trends Biotechnol DOI:10.1016/j.tibtech.2017.12.008

Diagnostic Potential of Imaging Flow Cytometry.

Publication TypeJournal Article
Year of Publication2018
AuthorsDoan, M, Vorobjev, I, Rees, P, Filby, A, Wolkenhauer, O, Goldfeld, AE, Lieberman, J, Barteneva, N, Carpenter, AE, Hennig, H
JournalTrends Biotechnol
Volume36
Issue7
Pages649-652
Date Published2018 07
ISSN1879-3096
KeywordsData Analysis, Deep Learning, Flow Cytometry, Humans, Image Processing, Computer-Assisted, Leukemia, Myeloid, Microscopy, Fluorescence, Neoplastic Cells, Circulating, Precision Medicine, Prognosis, Single Molecule Imaging, Single-Cell Analysis
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.

DOI10.1016/j.tibtech.2017.12.008
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/29395345?dopt=Abstract

Alternate JournalTrends Biotechnol.
PubMed ID29395345
Grant ListBB/N005163 / / Biotechnology and Biological Sciences Research Council / United Kingdom