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  • Biophotonics Congress: Optics in the Life Sciences 2023 (OMA, NTM, BODA, OMP, BRAIN)
  • Technical Digest Series (Optica Publishing Group, 2023),
  • paper NTu1C.3
  • https://doi.org/10.1364/NTM.2023.NTu1C.3

Optimizing Imaging Throughput and Resolution in Light Sheet Microscopy Using Deep-learning-based Beam Shape Translation

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Abstract

A conditional generative adversarial network (cGAN) approach to optimize resolution or contrast and field-of-view (FOV) in beam-scanned light sheet microscopy by beam shape translation is demonstrated. Large FOV images acquired with collimated (pencil) beam (weakly-focused) illumination are used to predict large FOV, but higher contrast, images mimicking Gaussian-beam (highly focused) illumination. In this way, imaging throughput and resolution is improved.

© 2023 The Author(s)

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