  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.
