Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,727 bioRxiv papers from 308,727 authors.
Within the family of super-resolution (SR) fluorescence microscopy, single-molecule localization microscopies (PALM, STORM and their derivatives) afford among the highest spatial resolution (approximately 5 to 10 nm), but often with moderate temporal resolution. The high spatial resolution relies on the adequate accumulation of precise localizations of bright fluorophores, which requires the bright fluorophores to possess a relatively low spatial density. Several methods have demonstrated localization at higher densities in both two dimensions (2D)[3, 4] and three dimensions (3D)[5-7]. Additionally, with further advancements, such as functional super-resolution[8, 9] and point spread function (PSF) engineering with[8-11] or without multi-channel observations, extra information (spectra, dipole orientation) can be encoded and recovered at the single molecule level. However, such advancements are not fully extended for high-density localizations in 3D. In this work, we adopt sparse recovery using simple matrix/vector operations, and propose a systematic progressive refinement method (dubbed as PRIS) for 3D high-density reconstruction. Our method allows for localization reconstruction using experimental PSFs that include the spatial aberrations and fingerprint patterns of the PSFs. We generalized the method for PSF engineering, multi-channel and multi-species observations using different forms of matrix concatenations. Reconstructions with both double-helix and astigmatic PSFs, for both single and biplane settings are demonstrated, together with the recovery capability for a mixture of two different color species.
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