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Volume 41 Issue 3, March 2023

Super-resolution imaging

Artistic rendering of a system for noise reduction in super-resolution images. Qiao et al. incorporate prior knowledge of illumination patterns into a deep learning algorithm and apply this method to sustained live cell imaging.

See Qiao et al.

Image: Dong Li, Institute of Biophysics, CAS; Chang Qiao, Tsinghua University. Cover Design: Erin Dewalt.

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  • We integrated the pre-characterized physical model of super-resolution (SR) microscopy into a deep neural network to guide the denoising of raw images for high-quality SR image reconstruction. This approach enabled us to investigate a wide variety of fragile and rapidly evolving bioprocesses at ultrahigh spatiotemporal resolution over extended imaging times.

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