scholarly journals Far-field transient absorption nanoscopy with sub-50  nm optical super-resolution

Optica ◽  
2020 ◽  
Vol 7 (10) ◽  
pp. 1402
Author(s):  
Yali Bi ◽  
Chi Yang ◽  
Lei Tong ◽  
Haozheng Li ◽  
Boyu Yu ◽  
...  
2021 ◽  
Author(s):  
Michael Weber ◽  
Marcel Leutenegger ◽  
Stefan Stoldt ◽  
Stefan Jakobs ◽  
Tiberiu S. Mihaila ◽  
...  

AbstractWe introduce MINSTED, a fluorophore localization and super-resolution microscopy concept based on stimulated emission depletion (STED) that provides spatial precision and resolution down to the molecular scale. In MINSTED, the intensity minimum of the STED doughnut, and hence the point of minimal STED, serves as a movable reference coordinate for fluorophore localization. As the STED rate, the background and the required number of fluorescence detections are low compared with most other STED microscopy and localization methods, MINSTED entails substantially less fluorophore bleaching. In our implementation, 200–1,000 detections per fluorophore provide a localization precision of 1–3 nm in standard deviation, which in conjunction with independent single fluorophore switching translates to a ~100-fold improvement in far-field microscopy resolution over the diffraction limit. The performance of MINSTED nanoscopy is demonstrated by imaging the distribution of Mic60 proteins in the mitochondrial inner membrane of human cells.


2018 ◽  
Vol 26 (7) ◽  
pp. 8095 ◽  
Author(s):  
Katrine S. Rogers ◽  
Konstantinos N. Bourdakos ◽  
Guang Hui Yuan ◽  
Sumeet Mahajan ◽  
Edward T. F. Rogers

2022 ◽  
Vol 11 (1) ◽  
Author(s):  
Fei Wang ◽  
Chenglong Wang ◽  
Mingliang Chen ◽  
Wenlin Gong ◽  
Yu Zhang ◽  
...  

AbstractGhost imaging (GI) facilitates image acquisition under low-light conditions by single-pixel measurements and thus has great potential in applications in various fields ranging from biomedical imaging to remote sensing. However, GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image, imposing a practical limit for its applications. Here we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural network. The resulting hybrid neural network does not need to pre-train on any dataset, and allows the reconstruction of a far-field image with the resolution beyond the diffraction limit. Furthermore, the physical model imposes a constraint to the network output, making it effectively interpretable. We experimentally demonstrate the proposed GI technique by imaging a flying drone, and show that it outperforms some other widespread GI techniques in terms of both spatial resolution and sampling ratio. We believe that this study provides a new framework for GI, and paves a way for its practical applications.


2005 ◽  
Vol 59 (7) ◽  
pp. 868-872 ◽  
Author(s):  
Takeshi Watanabe ◽  
Yoshinori Iketaki ◽  
Takashige Omatsu ◽  
Kimihisa Yamamoto ◽  
Masaaki Fujii

The two-point resolution of a novel two-color far-field super-resolution fluorescence microscopy was evaluated by measuring fluorescent beads 100 nm in diameter. This microscopy is based on a combination of two-color fluorescence dip spectroscopy and a phase-modulation technique for a laser beam. By simply introducing two-color laser light, the size of the fluorescent image of a bead was shrunk down to a diameter of 250 nm from the diffraction-limited image with a diameter of 360 nm. For two closely adjacent fluorescent beads with a separation distance of 350 nm, the two-color microscope clearly gave separated fluorescence images, while the conventional one-color fluorescence microscope could not resolve them. It has been proved that our technique breaks Rayleigh's diffraction limit.


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