optical imaging
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Synapse ◽  
2022 ◽  
Author(s):  
Yuki Kirihara ◽  
Manabu Zama ◽  
Satoshi Fujita ◽  
Shouhei Ogisawa ◽  
Shuichi Nishikubo ◽  
...  

2022 ◽  
Vol 11 (1) ◽  
Author(s):  
Hojun Lee ◽  
Seokchan Yoon ◽  
Pascal Loohuis ◽  
Jin Hee Hong ◽  
Sungsam Kang ◽  
...  

AbstractDeep-tissue optical imaging suffers from the reduction of resolving power due to tissue-induced optical aberrations and multiple scattering noise. Reflection matrix approaches recording the maps of backscattered waves for all the possible orthogonal input channels have provided formidable solutions for removing severe aberrations and recovering the ideal diffraction-limited spatial resolution without relying on fluorescence labeling and guide stars. However, measuring the full input–output response of the tissue specimen is time-consuming, making the real-time image acquisition difficult. Here, we present the use of a time-reversal matrix, instead of the reflection matrix, for fast high-resolution volumetric imaging of a mouse brain. The time-reversal matrix reduces two-way problem to one-way problem, which effectively relieves the requirement for the coverage of input channels. Using a newly developed aberration correction algorithm designed for the time-reversal matrix, we demonstrated the correction of complex aberrations using as small as 2% of the complete basis while maintaining the image reconstruction fidelity comparable to the fully sampled reflection matrix. Due to nearly 100-fold reduction in the matrix recording time, we could achieve real-time aberration-correction imaging for a field of view of 40 × 40 µm2 (176 × 176 pixels) at a frame rate of 80 Hz. Furthermore, we demonstrated high-throughput volumetric adaptive optical imaging of a mouse brain by recording a volume of 128 × 128 × 125 µm3 (568 × 568 × 125 voxels) in 3.58 s, correcting tissue aberrations at each and every 1 µm depth section, and visualizing myelinated axons with a lateral resolution of 0.45 µm and an axial resolution of 2 µm.


Author(s):  
Shasha Liu ◽  
Mengqi Lv ◽  
Haoran Li ◽  
Sa Wang ◽  
Chengdong Feng ◽  
...  

2022 ◽  
pp. 195-260
Author(s):  
Lakshminarayan Hazra
Keyword(s):  

2022 ◽  
Author(s):  
G. U. Raju ◽  
Santosh Billur ◽  
I .G. Siddhalingeshwar ◽  
Narendra Patil

2022 ◽  
Vol 6 (1) ◽  
pp. 50-61
Author(s):  
Haeni Lee ◽  
Jaeheung Kim ◽  
Hyung-Hoi Kim ◽  
Chang-Seok Kim ◽  
Jeesu Kim

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