Fluorescence microscopy is a powerful tool to measure molecular specific information in biological samples. However, most biological tissues are highly heterogeneous because of refractive index (RI) differences and thus degrade the signal-to-noise ratio of fluorescence images. At the same time, RI is an intrinsic optical property of label free biological tissues that quantitatively relates to cell morphology, mass, and stiffness. Conventional imaging techniques measure fluorescence and RI of biological samples separately. Here, we develop a new computational hybrid imaging method based on a multi-slice model of multiple scattering that reconstructs 3D fluorescence and 3D RI from the same dataset of fluorescence images. Our method not only bridges the gap between fluorescence and RI imaging and provides a panoramic view of the biological samples, but also can digitally correct multiple scattering effect of fluorescence images from the reconstructed 3D RI. Computational hybrid imaging opens a unique avenue beyond conventional imaging techniques.
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