Bayesian MINFLUX localization microscopy
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866910133873803264 |
|---|---|
| author | Schultze, Steffen Grubmüller, Helmut |
| author_facet | Schultze, Steffen Grubmüller, Helmut |
| contents | MINFLUX microscopy allows for localization of fluorophores with nanometer precision using targeted scanning with an illumination profile with a minimum. However, current scanning patterns and the overall procedure are based on heuristics, and may therefore be suboptimal. Here we present a rigorous Bayesian that offers maximal resolutions from either minimal detected photons or minimal exposures. We estimate using simulated localization runs that this approach should reduce the number of photons required for 1 nm resolution by a factor of about four. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_25654 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Bayesian MINFLUX localization microscopy Schultze, Steffen Grubmüller, Helmut Computational Physics Data Analysis, Statistics and Probability MINFLUX microscopy allows for localization of fluorophores with nanometer precision using targeted scanning with an illumination profile with a minimum. However, current scanning patterns and the overall procedure are based on heuristics, and may therefore be suboptimal. Here we present a rigorous Bayesian that offers maximal resolutions from either minimal detected photons or minimal exposures. We estimate using simulated localization runs that this approach should reduce the number of photons required for 1 nm resolution by a factor of about four. |
| title | Bayesian MINFLUX localization microscopy |
| topic | Computational Physics Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2510.25654 |