Improving axial resolution in SIM using deep learning
File(s)
Supporting information
Accepted version
Author(s)
Boland, M
Cohen, E
Flaxman, S
Neil, M
Type
Journal Article
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 demonstrate our method is robust to noise & evaluate it against two point cases and axial gratings. Finally, we discuss potential adaptions of the method to further improve resolution.
Date Acceptance
2021-01-12
ISSN
1364-503X
Publisher
The Royal Society
Journal / Book Title
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Copyright Statement
Copyright, the author(s)
License URL
Subjects
General Science & Technology
Publication Status
Accepted
Date Publish Online
2021-04-26