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Artificial intelligence for microscopy: what you should know

von Chamier, L; Laine, RF; Henriques, R; (2019) Artificial intelligence for microscopy: what you should know. Biochemical Society Transactions 10.1042/BST20180391. (In press). Green open access

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Abstract

Artificial Intelligence based on Deep Learning (DL) is opening new horizons in biomedical research and promises to revolutionize the microscopy field. It is now transitioning from the hands of experts in computer sciences to biomedical researchers. Here, we introduce recent developments in DL applied to microscopy, in a manner accessible to non-experts. We give an overview of its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how DL shows an outstanding potential to push the limits of microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are discussed, along with the future directions expected in this field.

Type: Article
Title: Artificial intelligence for microscopy: what you should know
Open access status: An open access version is available from UCL Discovery
DOI: 10.1042/BST20180391
Publisher version: https://doi.org/10.1042/BST20180391
Language: English
Additional information: © 2019 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
Keywords: artificial intelligence, classification, live-cell imaging, machine learning, segmentation, super-resolution microscopy
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
URI: http://discovery.ucl.ac.uk/id/eprint/10079602
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