International audienceThree-dimensional fluorescence microscopy based on Nyquist sampling of focal planes faces harsh trade-offs between acquisition time, light exposure, and signal-to-noise. We propose a 3D compressed sensing approach that uses temporal modulation of the excitation intensity during axial stage sweeping and can be adapted to fluorescence microscopes without hardware modification. We describe implementations on a lattice light sheet microscope and an epifluorescence microscope, and show that images of beads and biological samples can be reconstructed with a 5-10 fold reduction of light exposure and acquisition time. Our scheme opens a new door towards faster and less damaging 3D fluorescence microscopy., "Metamaterial apertu...
Computational imaging involves simultaneously designing optical hardware and reconstruction software...
We present high-resolution, high-speed fluorescence lifetime imaging microscopy (FLIM) of live cells...
Three-dimensional structured illumination microscopy (3D-SIM) requires at least fifteen raw images t...
International audienceThree-dimensional fluorescence microscopy based on Nyquist sampling of focal p...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Computational imaging involves simultaneously designing optical hardware and reconstruction software...
We present high-resolution, high-speed fluorescence lifetime imaging microscopy (FLIM) of live cells...
Three-dimensional structured illumination microscopy (3D-SIM) requires at least fifteen raw images t...
International audienceThree-dimensional fluorescence microscopy based on Nyquist sampling of focal p...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
International audienceIn this work, we introduce an original strategy to apply the Compressed Sensin...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from...
Computational imaging involves simultaneously designing optical hardware and reconstruction software...
We present high-resolution, high-speed fluorescence lifetime imaging microscopy (FLIM) of live cells...
Three-dimensional structured illumination microscopy (3D-SIM) requires at least fifteen raw images t...