High-speed label-free multimode-fiber-based compressive imaging beyond the diffraction limit

Ksenia Abrashitova*, Lyubov V. Amitonova

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Glass fibers are miniature optical components that serve as ultra-narrow endoscopy probes. Ideally, one would want to perform imaging through a fiber at the highest achievable resolution and speed. State-of-the-art super-resolution techniques have shattered the diffraction limit, but more than twofold improvement requires fluorescent labeling and a long acquisition time. Moreover, it is challenging to implement super-resolution microscopy in a fiber format. Here we present fiber-based label-free video-rate imaging at more than 2-fold higher resolution than the diffraction limit. Our work paves the way to rapid, sub-wavelength endo-microscopy in unlabeled live specimens.

Original languageEnglish
Pages (from-to)10456-10469
Number of pages14
JournalOptics Express
Volume30
Issue number7
Early online date15 Mar 2022
DOIs
Publication statusPublished - 28 Mar 2022

Bibliographical note

Funding Information:
Acknowledgments. This work has been carried out within ARCNL, a public-private partnership between UvA, VU, NWO and ASML, and was financed by ‘Toeslag voor Topconsortia voor Kennis en Innovatie (TKI)’ from the Dutch Ministry of Economic Affairs and Climate Policy. We thank Sergey Amitonov (TU Delft) for custom-made samples, Gerwin Osnabrugge (ARCNL) for fruitful discussions and Marco Seynen (AMOLF) for his help in programming the software.

Publisher Copyright:
© 2022 Optica Publishing Group.

Funding

Acknowledgments. This work has been carried out within ARCNL, a public-private partnership between UvA, VU, NWO and ASML, and was financed by ‘Toeslag voor Topconsortia voor Kennis en Innovatie (TKI)’ from the Dutch Ministry of Economic Affairs and Climate Policy. We thank Sergey Amitonov (TU Delft) for custom-made samples, Gerwin Osnabrugge (ARCNL) for fruitful discussions and Marco Seynen (AMOLF) for his help in programming the software.

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