Deep learning for fluorescence lifetime predictions enables high-throughput in vivo imaging
Sofia Kapsiani, Nino F. Läubli, Edward Ward, Ana Fernández‐Villegas, Bismoy Mazumder, Clemens F. Kaminski, Gabriele S. Kaminski Schierle
FLIMngo, a deep learning model, enables fast and accurate fluorescence lifetime predictions from low-photon FLIM data, improving throughput and reducing phototoxicity for in vivo applications.
Journal of the American Chemical Society · Jun 14, 2025Peer-reviewedBiophysics