Programmable super-resolution pupil phase filter with a deformable mirror

2016 ◽  
Vol 14 (9) ◽  
pp. 091201-91206 ◽  
Author(s):  
Lina Zhao Lina Zhao ◽  
Yun Dai Yun Dai ◽  
Junlei Zhao Junlei Zhao ◽  
Fei Xiao Fei Xiao ◽  
Xiaojun Zhang Xiaojun Zhang ◽  
...  
2017 ◽  
Vol 54 (4) ◽  
pp. 041801
Author(s):  
赵丽娜 Zhao Lina ◽  
戴云 Dai Yun ◽  
赵军磊 Zhao Junlei ◽  
肖飞 Xiao Fei ◽  
赵豪欣 Zhao Haoxin ◽  
...  

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Vytautas Navikas ◽  
Adrien C. Descloux ◽  
Kristin S. Grussmayer ◽  
Sanjin Marion ◽  
Aleksandra Radenovic

Abstract A variety of modern super-resolution microscopy methods provide researchers with previously inconceivable biological sample imaging opportunities at a molecular resolution. All of these techniques excel at imaging samples that are close to the coverslip, however imaging at large depths remains a challenge due to aberrations caused by the sample, diminishing the resolution of the microscope. Originating in astro-imaging, the adaptive optics (AO) approach for wavefront shaping using a deformable mirror is gaining momentum in modern microscopy as a convenient approach for wavefront control. AO has the ability not only to correct aberrations but also enables engineering of the PSF shape, allowing localization of the emitter axial position over several microns. In this study, we demonstrate remote focusing as another AO benefit for super-resolution microscopy. We show the ability to record volumetric data (45 × 45 × 10 µm), while keeping the sample axially stabilized using a standard widefield setup with an adaptive optics addon. We processed the data with single-molecule localization routines and/or computed spatiotemporal correlations, demonstrating subdiffraction resolution.


2006 ◽  
Vol 133 ◽  
pp. 645-648 ◽  
Author(s):  
B. E. Kruschwitz ◽  
R. Jungquist ◽  
J. Qiao ◽  
S. Abbey ◽  
S. E. Dean ◽  
...  

Acta Naturae ◽  
2017 ◽  
Vol 9 (4) ◽  
pp. 42-51
Author(s):  
S. S. Ryabichko ◽  
◽  
A. N. Ibragimov ◽  
L. A. Lebedeva ◽  
E. N. Kozlov ◽  
...  

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