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Deep learning-enhanced snapshot hyperspectral confocal microscopy imaging system

Version 2 2024-04-01, 18:22
Version 1 2024-04-01, 18:21
Posted on 2024-04-01 - 18:22
Laser-scanning confocal hyperspectral microscopy is a powerful technique to identify the different sample constituents and their spatial distribution in three-dimensional (3D). However, it suffers from low imaging speed because of the mechanical scanning methods. To overcome this challenge, we propose a snapshot hyperspectral confocal microscopy imaging system (SHCMS). It combined coded illumination microscopy based on a digital micromirror device (DMD) with a snapshot hyperspectral confocal neural network (SHCNet) to realize single-shot confocal hyperspectral imaging. With SHCMS, high-contrast 160-bands confocal hyperspectral images of potato tuber autofluorescence can be collected by only single-shot, which is almost 5 times improvement in the number of spectral channels than previously reported methods. Moreover, our approach can efficiently record hyperspectral volumetric imaging due to the optical sectioning capability. This fast high-resolution hyperspectral imaging method may pave the way for real-time highly multiplexed biological imaging.


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Shuai Liu
Wenzhen Zhou
hao sha
Xiaochen Feng
Bin Chen
Jian Zhang
Sanyang Han
Xiu Li
yongbing zhang


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