Deep learning enables structured illumination microscopy with low light levels and enhanced speed
Keyword(s):
AbstractUsing deep learning to augment structured illumination microscopy (SIM), we obtained a fivefold reduction in the number of raw images required for super-resolution SIM, and generated images under extreme low light conditions (100X fewer photons). We validated the performance of deep neural networks on different cellular structures and achieved multi-color, live-cell super-resolution imaging with greatly reduced photobleaching.
2020 ◽
Vol 52
(1)
◽
pp. 369-393
2021 ◽
2021 ◽