View-channel-depth light-field microscopy: real-time volumetric reconstruction of biological dynamics by deep learning
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AbstractLight-field microscopy has emerged as a technique of choice for high-speed volumetric imaging of fast biological processes. However, artefacts, non-uniform resolution, and a slow reconstruction speed have limited its full capabilities for in toto extraction of the dynamic spatiotemporal patterns in samples. Here, we combined a view-channel-depth (VCD) neural network with light-field microscopy to mitigate these limitations, yielding artefact-free three-dimensional image sequences with uniform spatial resolution and three-order-higher video-rate reconstruction throughput. We imaged neuronal activities across moving C. elegans and blood flow in a beating zebrafish heart at single-cell resolution with volume rates up to 200 Hz.
2004 ◽
Vol 126
(4)
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pp. 813-821
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2016 ◽
Vol 28
(4)
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pp. 523-532
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2020 ◽
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2021 ◽
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