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bioRxiv · 10.1101/255695

Sub-voxel light-sheet microscopy for high-resolution, high-throughput volumetric imaging of large biomedical specimens

Fei, P.·Nie, J.·Lee, J.·Ding, Y.·Li, S.·Yu, Z.·Zhang, H.·Hagiwara, M.·Yu, T.·Segura, T.·Ho, C.-M.·Zhu, D.·Hsiai, T. K.
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Abstract

A key challenge when imaging whole biomedical specimens is how to quickly obtain massive cellular information over a large field of view (FOV). Here, we report a sub-voxel light-sheet microscopy (SLSM) method enabling high-throughput volumetric imaging of mesoscale specimens at cellular-resolution. A non-axial, continuous scanning strategy is used to rapidly acquire a stack of large-FOV images with three-dimensional (3-D) nanoscale shifts encoded. Then by adopting a sub-voxel-resolving procedure, the SLSM method models these low-resolution, cross-correlated images in the spatial domain and iteratively recovers a 3-D image with improved resolution throughout the sample. This technique can surpass the optical limit of a conventional light-sheet microscope by more than three times, with high acquisition speeds of gigavoxels per minute. As demonstrated by quick reconstruction (minutes to hours) of various samples, e.g., 3-D cultured cells, an intact mouse heart, mouse brain, and live zebrafish embryo, the SLSM method presents a high-throughput way to circumvent the tradeoff between intoto mapping of large-scale tissue (>100 mm3) and isotropic imaging of single-cell (~1-m resolution). It also eliminates the need of complicated mechanical stitching or precisely modulated illumination, using a simple light-sheet setup and fast graphics-processing-unit (GPU)-based computation to achieve high-throughput, high-resolution 3-D microscopy, which could be tailored for a wide range of biomedical applications in pathology, histology, neuroscience, etc.

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Fei, P., Nie, J., Lee, J., Ding, Y., Li, S., Yu, Z., Zhang, H., Hagiwara, M., Yu, T., Segura, T., Ho, C.-M., Zhu, D., Hsiai, T. K.. 2018-01-29. Sub-voxel light-sheet microscopy for high-resolution, high-throughput volumetric imaging of large biomedical specimens. https://doi.org/10.1101/255695

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