von Chamier, L;
Laine, RF;
Henriques, R;
(2019)
Artificial intelligence for microscopy: what you should know.
Biochemical Society Transactions
, 47
(4)
pp. 1029-1040.
10.1042/BST20180391.
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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 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 > Lab for Molecular Cell Bio MRC-UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10079602 |
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