Author Affiliations
1 Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
2 Bauman Moscow State Technical University, Moscow 105005, Russia
3 Institute for Regenerative Medicine, Sechenov University, Moscow 119991, Russia
4 Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia
5 Research Institute of Human Morphology, Moscow 117418, Russia
6 School of Precision Instrument and Optoelectronic Engineering, Tianjin University, Tianjin 300000, China
7 College of Materials Science and Engineering, Sichuan University, Chengdu 610000, China
8 Science Medical Center, Saratov State University, Saratov 410012, Russia
9 Institute of Precision Mechanics and Control, FRC "Saratov Scientific Centre of the Russian Academy of Sciences", Saratov 410028, Russia
Terahertz (THz) technology offers novel opportunities in biology and medicine, thanks to the unique features of THz-wave interactions with tissues and cells. Among them, we particularly notice strong sensitivity of THz waves to the tissue water, as a medium for biochemical reactions and a main endogenous marker for THz spectroscopy and imaging. Tissues of the brain have an exceptionally high content of water. This factor, along with the features of the structural organization and biochemistry of neuronal and glial tissues, makes the brain an exciting subject to study in the THz range. In this paper, progress and prospects of THz technology in neurodiagnostics are overviewed, including diagnosis of neurodegenerative disease, myelin deficit, tumors of the central nervous system (with an emphasis on brain gliomas), and traumatic brain injuries. Fundamental and applied challenges in study of the THz-wave – brain tissue interactions and development of the THz biomedical tools and systems for neurodiagnostics are discussed.
THz technology THz spectroscopy and imaging superresolution imaging biophotonics brain neurodiagnosis tumor glioma neurodegenerative diseases brain injury light scattering 
Opto-Electronic Advances
2023, 6(5): 220071
Yu He 1†Yunhua Yao 1Yilin He 1Zhengqi Huang 1[ ... ]Shian Zhang 1,5,6,*
Author Affiliations
1 East China Normal University, School of Physics and Electronic Science, State Key Laboratory of Precision Spectroscopy, Shanghai, China
2 Shenzhen University, Institute of Microscale Optoelectronics, Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology, Shenzhen, China
3 Peking University, Biomedical Engineering Department, Beijing, China
4 Peking University, School of Physics, State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics, Beijing, China
5 East China Normal University, Joint Research Center of Light Manipulation Science and Photonic Integrated Chip of East China Normal University and Shandong Normal University, Shanghai, China
6 Shanxi University, Collaborative Innovation Center of Extreme Optics, Taiyuan, China
Structured illumination microscopy (SIM) has been widely applied in the superresolution imaging of subcellular dynamics in live cells. Higher spatial resolution is expected for the observation of finer structures. However, further increasing spatial resolution in SIM under the condition of strong background and noise levels remains challenging. Here, we report a method to achieve deep resolution enhancement of SIM by combining an untrained neural network with an alternating direction method of multipliers (ADMM) framework, i.e., ADMM-DRE-SIM. By exploiting the implicit image priors in the neural network and the Hessian prior in the ADMM framework associated with the optical transfer model of SIM, ADMM-DRE-SIM can further realize the spatial frequency extension without the requirement of training datasets. Moreover, an image degradation model containing the convolution with equivalent point spread function of SIM and additional background map is utilized to suppress the strong background while keeping the structure fidelity. Experimental results by imaging tubulins and actins show that ADMM-DRE-SIM can obtain the resolution enhancement by a factor of ∼1.6 compared to conventional SIM, evidencing the promising applications of ADMM-DRE-SIM in superresolution biomedical imaging.
structured illumination microscopy superresolution imaging resolution enhancement untrained neural network 
Advanced Photonics Nexus
2023, 2(4): 046005
1 南昌大学信息工程学院, 江西 南昌 330031
2 中国科学院上海应用物理研究所物理生物实验室, 上海 201800
显微 空间分辨率 环形光瞳 荧光辐射差分显微技术 超分辨成像 microscopy spatial resolution annular pupil fluorescence emission difference microscopy superresolution imaging 
2019, 39(7): 0718001
1 北京理工大学 光电学院 光电成像技术与系统教育部重点实验室,北京 100081
2 空军航空大学 飞行基础训练基地基础部,吉林 长春 130022
几何超分辨 超分辨成像 光学掩模 频谱编码 CCD实际模型 geometric superresolution superresolution imaging optical mask spectrum encoding CCD practical model 
光学 精密工程
2014, 22(8): 2026
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing 100084, China
scanning near-field optical microscopy (SNOM) near-field optical (NFO) measurement superresolution imaging near-field spectroscopy nano-optics nanophotonics 
Frontiers of Optoelectronics
2012, 5(2): 171

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