Single-molecule localization microscopy (SMLM) has revolutionized nanoscale imaging. Specifically, 3D SMLM is a powerful tool for volumetric nanoscopy. However, accessibility and usability remain major hurdles: neural-net-based reconstruction algorithms still require expertise to use properly, and optical components for wavefront shaping are difficult to obtain. Recent advances from our lab addressing both optics and computation, enable broader adoption and improved performance: On the software side, we developed automated pipelines that provide one-click reconstructions for high-density 2D and 3D SMLM. By automatically extracting imaging parameters and selecting pre-trained models, they yield reconstructions matching or surpassing manually tuned deep-learning methods, while reducing computation time and minimizing required expertise. On the hardware side, we developed additive manufacturing techniques of transparent materials with near-index matching, enabling fabrication of diffractive optical elements at unprecedented speeds and simplicity. We demonstrate fabrication of complex phase masks, high-order vortex plates, microlens arrays, and multicolor elements with high photon efficiency. Imaging applications demonstrated include multicolor localization microscopy and MINSTED. Together, these developments significantly lower adoption barriers for 3D SMLM, contributing to the democratization of such techniques.
Yoav Shechtman (Sun,) studied this question.