Experimentally unsupervised deconvolution for light-sheet microscopy with propagation-invariant beams
P. Wijesinghe, S. Corsetti, D. J. X. Chow, S. Sakata, K. Dunning, K. Dholakia
This paper introduces a deep learning deconvolution method for light-sheet microscopy using propagation-invariant beams, trained with physics-based images and unpaired data, achieving improved image contrast without requiring extensive paired training data.
bioRxiv · May 26, 2021Biophysics