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Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging

Authors :
Edward N. Ward
Lisa Hecker
Charles N. Christensen
Jacob R. Lamb
Meng Lu
Luca Mascheroni
Chyi Wei Chung
Anna Wang
Christopher J. Rowlands
Gabriele S. Kaminski Schierle
Clemens F. Kaminski
Source :
Nature Communications, Vol 13, Iss 1, Pp 1-10 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Structured Illumination Microscopy allows for the visualization of biological structures at resolutions below the diffraction limit, but this imaging modality is still hampered by high experimental complexity. Here, the authors present a combination of interferometry and machine learning to construct a structured illumination microscope for super resolution imaging of dynamic sub-cellular biological structures in multiple colors.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723 and 34640339
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.66f1b12be34640339d1e4a7bd953ad1d
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-022-35307-0