Fast, multicolour optical sectioning over extended fields of view by combining interferometric SIM with machine learning
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. Currently, this optical-sectioning technique is limited by image reconstruction artefacts and the need for sequential imaging of multiple colour channels. We combine multicolour interferometric pattern generation with machine-learning processing, permitting high-contrast, real-time reconstruction of image data. The method is insensitive to background noise and unevenly phase-stepped illumination patterns. We validate the method in silico and demonstrate its application on diverse specimens, ranging from fixed and live biological cells to synthetic biosystems, imaging at up to 37 Hz across a 44 x 44 field of view.
Cite
@article{arxiv.2311.00089,
title = {Fast, multicolour optical sectioning over extended fields of view by combining interferometric SIM with machine learning},
author = {Edward N. Ward and Rebecca M. McClelland and Jacob R. Lamb and Roger Rubio-Sánchez and Charles N. Christensen and Bismoy Mazumder and Sofia Kapsiani and Luca Mascheroni and Lorenzo Di Michele and Gabriele S. Kaminski Schierle and Clemens F. Kaminski},
journal= {arXiv preprint arXiv:2311.00089},
year = {2023}
}