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Fast, multicolour optical sectioning over extended fields of view with patterned illumination and machine learning.

Accepted version
Peer-reviewed

Change log

Authors

McClelland, Rebecca M  ORCID logo  https://orcid.org/0000-0002-9102-8118
Lamb, Jacob R 
Rubio-Sánchez, Roger  ORCID logo  https://orcid.org/0000-0001-5574-5809
Christensen, Charles N  ORCID logo  https://orcid.org/0000-0002-5355-1063

Abstract

Structured illumination can reject out-of-focus signal from a sample, enabling high-speed and high-contrast imaging over large areas with widefield detection optics. However, this optical sectioning technique is currently limited by image reconstruction artefacts and poor performance at low signal-to-noise ratios. We combine multicolour interferometric pattern generation with machine learning to achieve high-contrast, real-time reconstruction of image data that is robust to background noise and sample motion. We validate the method in silico and demonstrate imaging of diverse specimens, from fixed and live biological samples to synthetic biosystems, reconstructing data live at 11 Hz across a 44 × 44μm2 field of view, and demonstrate image acquisition speeds exceeding 154 Hz.

Description

Keywords

5102 Atomic, Molecular and Optical Physics, 51 Physical Sciences

Journal Title

Biomed Opt Express

Conference Name

Journal ISSN

2156-7085
2156-7085

Volume Title

Publisher

Optica Publishing Group
Sponsorship
Engineering and Physical Sciences Research Council (EP/L015889/1)
Engineering and Physical Sciences Research Council (EP/H018301/1)
Wellcome Trust (089703/Z/09/Z)
Medical Research Council (MR/K015850/1)
Medical Research Council (MR/K02292X/1)
BBSRC (BB/X010228/1)
Royal Society (UF160152)
Royal Society (URF\R\221009)
Wellcome Trust (065807/Z/01/Z)
Wellcome Trust (203249/Z/16/Z)
Michael J. Fox Foundation (MJFF) (16238)
EPSRC (EP/S023046/1)
Engineering and Physical Sciences Research Council (EP/S022139/1)