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Large scale, high-throughput neuro imaging with voxel super-resolved light-sheet microscopy
1  school of optical and electronic information, huazhong university of science and technology

Abstract:

How to intoto extract the spatiotemporal information of massive cells when imaging whole organisms is a key challenge to modern light microscopy. Unlike popular epifluorescence microscopy methods, light-sheet fluorescent microscopy (LSFM) recently emerges as a technique of choice that uniquely limits excitation to the vicinity of the focal plane, providing high axial resolution and fast acquisition rate while minimizing the background and photo-damage. Here we present a voxel super-resolving reconstruction strategy in conjunction with an oblique light-sheet scanning approach to achieve three-dimensionally (3-D) enhanced resolution as well as reduced aliasing better suited to volumetric imaging of multi-cellular organisms. This reported method, termed oblique scanning light-sheet microscopy, uses fast GPU-based computation to address the general challenge of high-throughput, high-resolution microscopy that is originally coupled to the physical limitation of the system optics. As demonstrated by imaging of brain and neuron structures,  our method currently offers improved spatial resolution by ~3 folds compared to conventional LSFM images, high speeds up to nearly 2 volumes per minute, and the ability to circumvent the tradeoff between a over 100 mm3 large volume of macro specimen and ~2 μm isotropic resolution of cells.

Keywords: light-sheet fluorescent microscopy, high-throughput, super-resolution, chip-based scanning
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