Algorithmic super-resolution in the context of fluorescence microscopy is challenging due to the difficulty to reliably represent biological nanostructures in synthetically generated images. Bouchard and colleagues propose a deep learning model for live-cell imaging that can leverage auxiliary microscopy imaging tasks to guide and enhance reconstruction, while preserving the biological features of interest.
- Catherine Bouchard
- Theresa Wiesner
- Flavie Lavoie-Cardinal
