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

Author:

Ward Edward N.ORCID,McClelland Rebecca M.ORCID,Lamb Jacob R.,Rubio-Sánchez Roger1ORCID,Christensen Charles N.ORCID,Mazumder Bismoy,Kapsiani Sofia,Mascheroni Luca,Di Michele Lorenzo1,Kaminski Schierle Gabriele S.,Kaminski Clemens F.

Affiliation:

1. Imperial College London

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.

Funder

Michael J. Fox Foundation for Parkinson's Research

Alzheimer’s Research UK

Royal Society

H2020 European Research Council

Biotechnology and Biological Sciences Research Council

Infinitus Ltd.

Medical Research Council

Wellcome Trust

Engineering and Physical Sciences Research Council

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics,Biotechnology

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