Fast DNA-PAINT imaging using a deep neural network

• Verfasst von: Narayanasamy, Kaarjel K. [VerfasserIn]
• Verfasst von: Rahm, Johanna V. [VerfasserIn]
• Verfasst von: Tourani, Siddharth [VerfasserIn]
• Verfasst von: Heilemann, Mike [VerfasserIn]
• Titel: Fast DNA-PAINT imaging using a deep neural network
• Verf.angabe: Kaarjel K. Narayanasamy, Johanna V. Rahm, Siddharth Tourani & Mike Heilemann
• E-Jahr: 2022
• Jahr: 27 August 2022
• Umfang: 11 S.
• Fussnoten: Gesehen am 14.09.2022
• Titel Quelle: Enthalten in: Nature Communications
• Ort Quelle: [London] : Nature Publishing Group UK, 2010
• Jahr Quelle: 2022
• Band/Heft Quelle: 13(2022), Artikel-ID 5047, Seite 1-11
• ISSN Quelle: 2041-1723
• DOI: doi:10.1038/s41467-022-32626-0
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Image processing
• Sach-SW: Super-resolution microscopy
• K10plus-PPN: 1816607789

Abstract

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.