Imperial College London
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DrChristopherRowlands

Faculty of Engineering, Department of Bioengineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 1331c.rowlands Website CV

 
 
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Location

 

3.15Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Ward:2022:10.1038/s41467-022-35307-0,
author = {Ward, EN and Hecker, L and Christensen, CN and Lamb, JR and Lu, M and Mascheroni, L and Chung, CW and Wang, A and Rowlands, CJ and Schierle, GSK and Kaminski, CF},
doi = {10.1038/s41467-022-35307-0},
journal = {Nat Commun},
title = {Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.},
url = {http://dx.doi.org/10.1038/s41467-022-35307-0},
volume = {13},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at once, which reduces imaging speed. Furthermore, there is substantial experimental complexity in setting up SIM systems, preventing a widespread adoption. Here, we present Machine-learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for live cell super-resolution imaging at high speed and in multiple colors. The instrument is based on an interferometer design in which illumination patterns are generated, rotated, and stepped in phase through movement of a single galvanometric mirror element. The design is robust, flexible, and works for all wavelengths. We complement the unique properties of the microscope with an open source machine-learning toolbox that permits real-time reconstructions to be performed, providing instant visualization of super-resolved images from live biological samples.
AU  - Ward,EN
AU  - Hecker,L
AU  - Christensen,CN
AU  - Lamb,JR
AU  - Lu,M
AU  - Mascheroni,L
AU  - Chung,CW
AU  - Wang,A
AU  - Rowlands,CJ
AU  - Schierle,GSK
AU  - Kaminski,CF
DO  - 10.1038/s41467-022-35307-0
PY  - 2022///
TI  - Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.
T2  - Nat Commun
UR  - http://dx.doi.org/10.1038/s41467-022-35307-0
UR  - https://www.ncbi.nlm.nih.gov/pubmed/36543776
VL  - 13
ER  -
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