We develop computational methods to overcome the conventional resolution limits of fluorescence microscopy, revealing cellular structures hidden by the diffraction barrier. Integrating advanced image processing with model-aware deep learning, we extract meaningful biological insights from seemingly imperfect or limited microscopy data. This research enables scientists to visualise nanoscale phenomena with unprecedented clarity, deepening our understanding of fundamental biological processes.

Luca Calatroni DIBRIS, Università di Genova

Giuseppe Vicidomini’s Molecular Microscopy and Spectroscopy teamIstituto Italiano di Tecnologia, Italy
Sebastian Schaub CNRS, I3S, France
Laure Blanc-Féraud CNRS, LBDV, France