Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning

We report a deep-learning-based imaging technique to predict 3D multiplexed fluorescence signals based on label-free refractive index measurements. We demonstrate the retrieval of specific subcellular information without exogenous labeling or staining, enabling multiplexed molecular imaging across various spatiotemporal scales.