Fast DNA-PAINT imaging using a deep neural network

  • DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.

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Metadaten
Author:Kaarjel K. NarayanasamyORCiDGND, Johanna Viola RahmORCiDGND, Siddharth Tourani, Mike HeilemannORCiDGND
URN:urn:nbn:de:hebis:30:3-742279
DOI:https://doi.org/10.1038/s41467-022-32626-0
ISSN:2041-1723
Parent Title (German):Nature Communications
Publisher:Nature Publishing Group UK
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2022/08/27
Date of first Publication:2022/08/27
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/08/03
Volume:13
Issue:5047
Page Number:11
HeBIS-PPN:511237049
Institutes:Biochemie, Chemie und Pharmazie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0