Large-FOV 3D localization microscopy by spatially variant point spread function generation.
Journal
Science advances
ISSN: 2375-2548
Titre abrégé: Sci Adv
Pays: United States
ID NLM: 101653440
Informations de publication
Date de publication:
08 Mar 2024
08 Mar 2024
Historique:
medline:
8
3
2024
pubmed:
8
3
2024
entrez:
8
3
2024
Statut:
ppublish
Résumé
Accurate characterization of the microscopic point spread function (PSF) is crucial for achieving high-performance localization microscopy (LM). Traditionally, LM assumes a spatially invariant PSF to simplify the modeling of the imaging system. However, for large fields of view (FOV) imaging, it becomes important to account for the spatially variant nature of the PSF. Here, we propose an accurate and fast principal components analysis-based field-dependent 3D PSF generator (PPG3D) and localizer for LM. Through simulations and experimental three-dimensional (3D) single-molecule localization microscopy (SMLM), we demonstrate the effectiveness of PPG3D, enabling super-resolution imaging of mitochondria and microtubules with high fidelity over a large FOV. A comparison of PPG3D with a shift-variant PSF generator for 3D LM reveals a threefold improvement in accuracy. Moreover, PPG3D is approximately 100 times faster than existing PSF generators, when used in image plane-based interpolation mode. Given its user-friendliness, we believe that PPG3D holds great potential for widespread application in SMLM and other imaging modalities.
Identifiants
pubmed: 38457497
doi: 10.1126/sciadv.adj3656
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM