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In recent years, modulated illumination localization microscopy (MILM) methods have been proposed to provide around two-fold improvement in lateral localization precision over conventional single molecule localization microscopy methods with the same photon budget. However, MILM with laterally modulated illumination was so far reported in two-dimensional imaging modalities. To fully exploit its three-dimensional (3D) imaging potential, we propose a 3D Single-Molecule Modulated Illumination Localization Estimator (3D-SMILE) that uses the raw data measured from MILM, which has enabled a high localization precision that reaches the theoretical Cramér-Rao lower bound (CRLB) in all three dimensions. 3D-SMILE is based an optimal joint fitting algorithm implemented on a graphics processing unit (GPU) for acceleration. We have shown in simulations that the average lateral localization precision of 3D-SMILE has been improved by more than 3.5 folds over 3D-SMLM over an imaging depth range of around 1.2 μm.
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Hongfei Zhu, Yile Sun, Hanmeng Wu, Cuifang Kuang, Renjie Zhou, "Optimal fitting strategy for modulated illumination localization microscopy," Proc. SPIE 12435, Emerging Digital Micromirror Device Based Systems and Applications XV, 1243508 (15 March 2023); https://doi.org/10.1117/12.2648821