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Deep Hyperspectral microscopy based on structured light sheet

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Abstract

We describe a computational hyperspectral microscope based on a structured light sheet that is generated using a digital micromirror device only. To reduce the acquisition time, we consider a small number of structured patterns. We solve the resulting inverse problem using an unrolled deep neural network, which limits the loss of spatial resolution.

© 2022 The Author(s)

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