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arXiv · 2009.02264

Improving axial resolution in SIM using deep learning

Miguel Boland·Edward A. K. Cohen·Seth Flaxman·Mark A. A. Neil
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Abstract

Structured Illumination Microscopy is a widespread methodology to image live and fixed biological structures smaller than the diffraction limits of conventional optical microscopy. Using recent advances in image up-scaling through deep learning models, we demonstrate a method to reconstruct 3D SIM image stacks with twice the axial resolution attainable through conventional SIM reconstructions. We further evaluate our method for robustness to noise & generalisability to varying observed specimens, and discuss potential adaptions of the method to further improvements in resolution.

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Miguel Boland, Edward A. K. Cohen, Seth Flaxman, Mark A. A. Neil. 2021-02-18. Improving axial resolution in SIM using deep learning. https://arxiv.org/abs/2009.02264

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