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Abstract:
Light microscopy on dynamic samples, for example neural activity in the brain, often requires imaging volumes that extend over several 100 µm in axial direction at a rate of at least several tens of Hertz. Here, we develop a tomography approach for scanning fluorescence microscopy which allows recording a volume image in a single frame scan. Volumes are imaged by simultaneously recording four independent projections at different angles using temporally multiplexed, tilted Bessel beams. From the resulting projections, three-dimensional images are reconstructed using inverse Radon transforms combined with convolutional neural networks (U-net).
