Error-free coding of range gates for super-resolution three-dimensional imaging

Author(s):  
Martin Laurenzis ◽  
Emmanuel Bacher ◽  
Frank M. Christnacher
2015 ◽  
Vol 44 (3) ◽  
pp. 328001
Author(s):  
王锋 WANG Feng ◽  
罗建军 LUO Jian-jun ◽  
唐兴佳 TANG Xing-jia ◽  
李立波 LI Li-bo ◽  
胡炳樑 HU Bin-liang

ACS Nano ◽  
2020 ◽  
Vol 14 (11) ◽  
pp. 14999-15010
Author(s):  
Chan E Park ◽  
Youngbin Cho ◽  
In Cho ◽  
Hyunsu Jung ◽  
Byeongyeon Kim ◽  
...  

Author(s):  
Linyu Xu ◽  
Yanwei Zhang ◽  
Song Lang ◽  
Hongwei Wang ◽  
Huijie Hu ◽  
...  

Structured illumination microscopy (SIM) is a rapidly developing super-resolution technology. It has been widely used in various application fields of biomedicine due to its excellent two- and three-dimensional imaging capabilities. Furthermore, faster three-dimensional imaging methods are required to help enable more research-oriented living cell imaging. In this paper, a fast and sensitive three-dimensional structured illumination microscopy based on asymmetric three-beam interference is proposed. An innovative time-series acquisition method is employed to halve the time required to obtain each raw image. A segmented half-wave plate as a substantial linear polarization modulation method is applied to the three-dimensional SIM system for the first time. Although it needs to acquire 21 raw images instead of 15 to reconstruct one super-resolution image, the SIM setup proposed in this paper is 30% faster than the traditional spatial light modulator-SIM (SLM-SIM) in imaging each super-resolution image. The related theoretical derivation, hardware system, and verification experiment are elaborated in this paper. The stable and fast 3D super-resolution imaging method proposed in this paper is of great significance to the research of organelle interaction, intercellular communication, and other biomedical fields.


1996 ◽  
Vol 34 (1) ◽  
pp. 27
Author(s):  
Sue Yon Shim ◽  
Ki Joon Sung ◽  
Young Ju Kim ◽  
In Soo Hong ◽  
Myung Soon Kim ◽  
...  

Author(s):  
Lukas Helfen ◽  
Thilo F. Morgeneyer ◽  
Feng Xu ◽  
Mark N. Mavrogordato ◽  
Ian Sinclair ◽  
...  

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