Login / Signup

Universal inverse modelling of point spread functions for SMLM localization and microscope characterization.

Sheng LiuJianwei ChenJonas HellgothLucas-Raphael MüllerBoris FerdmanChristian KarrasDafei XiaoKeith A LidkeRainer HeintzmannYoav ShechtmanYiming LiJonas Ries
Published in: bioRxiv : the preprint server for biology (2023)
The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single molecule localization, aberration correction and deconvolution. Here we present uiPSF (universal inverse modelling of Point Spread Functions), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single molecule localization microscopy (SMLM). The resulting PSF model enables accurate 3D super-resolution imaging using SMLM. Additionally, uiPSF can be used to characterize and optimize a microscope system by quantifying the aberrations, including field-dependent aberrations, and resolutions. Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system or sample specific characteristics, e.g., the bead size, depth dependent aberrations and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single molecule blinking data.
Keyphrases
  • single molecule
  • living cells
  • high resolution
  • atomic force microscopy
  • electronic health record
  • big data
  • deep learning
  • optical coherence tomography
  • artificial intelligence
  • label free