Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments

Quantitative phase imaging suffers from a lack of specificity in label-free imaging. Here, the authors introduce Phase Imaging with Computational Specificity (PICS), a method that combines phase imaging with machine learning techniques to provide specificity in unlabeled live cells with automatic tr...

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Auteurs principaux:	Mikhail E. Kandel, Yuchen R. He, Young Jae Lee, Taylor Hsuan-Yu Chen, Kathryn Michele Sullivan, Onur Aydin, M. Taher A. Saif, Hyunjoon Kong, Nahil Sobh, Gabriel Popescu
Format:	article
Langue:	EN
Publié:	Nature Portfolio 2020
Sujets:	Science Q
Accès en ligne:	https://doaj.org/article/3e32cf5090894b6a8edfb3919fac738d
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spelling	oai:doaj.org-article:3e32cf5090894b6a8edfb3919fac738d2021-12-02T10:48:10ZPhase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments10.1038/s41467-020-20062-x2041-1723https://doaj.org/article/3e32cf5090894b6a8edfb3919fac738d2020-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-20062-xhttps://doaj.org/toc/2041-1723Quantitative phase imaging suffers from a lack of specificity in label-free imaging. Here, the authors introduce Phase Imaging with Computational Specificity (PICS), a method that combines phase imaging with machine learning techniques to provide specificity in unlabeled live cells with automatic training.Mikhail E. KandelYuchen R. HeYoung Jae LeeTaylor Hsuan-Yu ChenKathryn Michele SullivanOnur AydinM. Taher A. SaifHyunjoon KongNahil SobhGabriel PopescuNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Mikhail E. Kandel Yuchen R. He Young Jae Lee Taylor Hsuan-Yu Chen Kathryn Michele Sullivan Onur Aydin M. Taher A. Saif Hyunjoon Kong Nahil Sobh Gabriel Popescu Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
description	Quantitative phase imaging suffers from a lack of specificity in label-free imaging. Here, the authors introduce Phase Imaging with Computational Specificity (PICS), a method that combines phase imaging with machine learning techniques to provide specificity in unlabeled live cells with automatic training.
format	article
author	Mikhail E. Kandel Yuchen R. He Young Jae Lee Taylor Hsuan-Yu Chen Kathryn Michele Sullivan Onur Aydin M. Taher A. Saif Hyunjoon Kong Nahil Sobh Gabriel Popescu
author_facet	Mikhail E. Kandel Yuchen R. He Young Jae Lee Taylor Hsuan-Yu Chen Kathryn Michele Sullivan Onur Aydin M. Taher A. Saif Hyunjoon Kong Nahil Sobh Gabriel Popescu
author_sort	Mikhail E. Kandel
title	Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
title_short	Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
title_full	Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
title_fullStr	Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
title_full_unstemmed	Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments
title_sort	phase imaging with computational specificity (pics) for measuring dry mass changes in sub-cellular compartments
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/3e32cf5090894b6a8edfb3919fac738d
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Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments

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