Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 109, Issue 26, Pages E1679-E1687Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1119511109
Keywords
biological imaging; compressed sensing; computational imaging; sparse signals
Categories
Funding
- European Aeronautic Defence and Space Foundation
- EADS foundation
- conseil regional Aquitaine
- National Science Foundation [CCF-0963835]
- Air Force Office of Scientific Research [FA9550-09-1-0643]
- Office of Naval Research [N00014-09-1-0258]
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [0965028] Funding Source: National Science Foundation
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The mathematical theory of compressed sensing (CS) asserts that one can acquire signals from measurements whose rate is much lower than the total bandwidth. Whereas the CS theory is now well developed, challenges concerning hardware implementations of CS-based acquisition devices-especially in optics-have only started being addressed. This paper presents an implementation of compressive sensing in fluorescence microscopy and its applications to biomedical imaging. Our CS microscope combines a dynamic structured wide-field illumination and a fast and sensitive single-point fluorescence detection to enable reconstructions of images of fluorescent beads, cells, and tissues with undersampling ratios (between the number of pixels and number of measurements) up to 32. We further demonstrate a hyperspectral mode and record images with 128 spectral channels and undersampling ratios up to 64, illustrating the potential benefits of CS acquisition for higher-dimensional signals, which typically exhibits extreme redundancy. Altogether, our results emphasize the interest of CS schemes for acquisition at a significantly reduced rate and point to some remaining challenges for CS fluorescence microscopy.
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