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 trained 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-color super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule microscope and enables fast single-molecule super-resolution microscopy.

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Metadaten
Author:Kaarjel K. NarayanasamyORCiDGND, Johanna V. RahmORCiD, Siddharth Tourani, Mike HeilemannORCiDGND
URN:urn:nbn:de:hebis:30:3-729741
DOI:https://doi.org/10.1101/2021.11.20.469366
Parent Title (English):bioRxiv
Document Type:Preprint
Language:English
Date of Publication (online):2021/11/20
Date of first Publication:2021/11/20
Publishing Institution:Universit├Ątsbibliothek Johann Christian Senckenberg
Release Date:2023/07/22
Issue:2021.11.20.469366
Page Number:19
HeBIS-PPN:510563791
Institutes:Biochemie, Chemie und Pharmazie / Biochemie und Chemie
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universit├Ątspublikationen
Licence (German):License LogoCreative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International