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 out to some remaining
challenges for CS fluorescence microscopy.Comment: Submitted to Proceedings of the National Academy of Sciences of the
United States of Americ