A machine learning approach for online automated optimization of super-resolution optical microscopy.

TitleA machine learning approach for online automated optimization of super-resolution optical microscopy.
Publication TypeJournal Article
Year of Publication2018
AuthorsDurand A, Wiesner T, Gardner M-A, Robitaille L-É, Bilodeau A, Gagné C, De Koninck P, Lavoie-Cardinal F
JournalNat Commun
Volume9
Issue1
Pagination5247
Date Published2018 12 07
ISSN2041-1723
Abstract

Traditional approaches for finding well-performing parameterizations of complex imaging systems, such as super-resolution microscopes rely on an extensive exploration phase over the illumination and acquisition settings, prior to the imaging task. This strategy suffers from several issues: it requires a large amount of parameter configurations to be evaluated, it leads to discrepancies between well-performing parameters in the exploration phase and imaging task, and it results in a waste of time and resources given that optimization and final imaging tasks are conducted separately. Here we show that a fully automated, machine learning-based system can conduct imaging parameter optimization toward a trade-off between several objectives, simultaneously to the imaging task. Its potential is highlighted on various imaging tasks, such as live-cell and multicolor imaging and multimodal optimization. This online optimization routine can be integrated to various imaging systems to increase accessibility, optimize performance and improve overall imaging quality.

DOI10.1038/s41467-018-07668-y
Alternate JournalNat Commun
PubMed ID30531817
PubMed Central IDPMC6286316

Funding

Our research endeavors are made possible by the following agencies:

Canadian Institutes of Health Research - Instituts de recherche en santé du Canada Fonds de recherche du Québec – Nature et technologies (FRQNT)Fonds de la recherche en santé du Québec  Natural Sciences and Engineering Research Council of Canada (NSERC) - Conseil de recherche en sciences naturelles et en génie du Canada (CRSNG)innovation.caHuman Frontier Science ProgramCanada First Research Excellence FundSentinelle Nord