LAUSR

Abstract Single-molecule localization microscopy (SMLM) is a powerful method for the imaging of cellular structures. This modality delivers nanoscale resolution by sequentially activating a subset of fluorescent molecules and by extracting their super-resolved positions from the microscope images. The emission patterns of individual molecules can be distorted by the refractive-index (RI) map of the sample, which reduces the accuracy of the molecule localization if not accounted for. In this work, we show that one can exploit those sample-induced aberrations to reveal the structural information of the specimen. Our work is related to the optical diffraction tomography in that we aim to recover the RI map. To that end, we propose an optimization framework in which we reconstruct the RI map and optimize the positions of the molecules in a joint fashion. The benefits of our method are twofold. On one side, we effectively recover the RI map of the sample. On the other side, we further improve the molecule localization—the primary purpose of SMLM. We validate our joint-optimization framework on simulated data. Our results lay the foundation of an exciting and novel extension of SMLM.