Yile Sun 1†Hongfei Zhu 2Lu Yin 3Hanmeng Wu 1[ ... ]Xu Liu 1,5,7
Author Affiliations
1 Zhejiang University, College of Optical Science and Engineering, State Key Laboratory of Extreme Photonics and Instrumentation, Hangzhou, China
2 The Chinese University of Hong Kong, Department of Biomedical Engineering, Hong Kong, China
3 China Jiliang University, College of Optical and Electronic Technology, Hangzhou, China
4 Zhejiang University of Technology, Institute of Pharmacology, College of Pharmaceutical Sciences, Hangzhou, China
5 ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, China
6 Huazhong University of Science and Technology, Britton Chance Center for Biomedical Photonics-MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility-Wuhan National Laboratory for Optoelectronics, Wuhan, China
7 Shanxi University, Collaborative Innovation Center of Extreme Optics, Taiyuan, China
Imaging three-dimensional, subcellular structures with high axial resolution has always been the core purpose of fluorescence microscopy. However, trade-offs exist between axial resolution and other important technical indicators, such as temporal resolution, optical power density, and imaging process complexity. We report a new imaging modality, fluorescence interference structured illumination microscopy (FI-SIM), which is based on three-dimensional structured illumination microscopy for wide-field lateral imaging and fluorescence interference for axial reconstruction. FI-SIM can acquire images quickly within the order of hundreds of milliseconds and exhibit even 30 nm axial resolution in half the wavelength depth range without z-axis scanning. Moreover, the relatively low laser power density relaxes the requirements for dyes and enables a wide range of applications for observing fixed and live subcellular structures.
optical imaging super-resolution microscopy fluorescence interference structured illumination microscopy 
Advanced Photonics
2023, 5(5): 056007
Zewei Luo 1,2†Guodong Zang 1,2Ge Wu 1,2Mengting Kong 1,2[ ... ]Tongsheng Chen 1,2,*
Author Affiliations
1 South China Normal University, College of Biophotonics, MOE Key Laboratory of Laser Life Science, Guangzhou, China
2 South China Normal University, College of Biophotonics, Guangdong Key Laboratory of Laser Life Science, Guangzhou, China
Structured illumination-based super-resolution Förster resonance energy transfer microscopy (SIM-FRET) provides an approach to resolving molecular behavior localized in intricate biological structures in living cells. However, SIM reconstruction artifacts will decrease the quantitative analysis fidelity of SIM-FRET signals. To address these issues, we have developed a method called HiFi spectrum optimization SIM-FRET (HiFi-SO-SIM-FRET), which uses optimized Wiener parameters in the two-step spectrum optimization to suppress sidelobe artifacts and achieve super-resolution quantitative SIM-FRET. We validated our method by demonstrating its ability to reduce reconstruction artifacts while maintaining the accuracy of FRET signals in both simulated FRET models and live-cell FRET-standard construct samples. In summary, HiFi-SO-SIM-FRET provides a promising solution for achieving high spatial resolution and reducing SIM reconstruction artifacts in quantitative FRET imaging.
super-resolution structured illumination microscopy Förster resonance energy transfer living cells quantitative measurement 
Advanced Photonics Nexus
2023, 2(5): 056008
深圳大学物理与光电工程学院,深圳市光子学与生物光子学重点实验室,光电子器件与系统教育部/广东省重点实验室,广东 深圳 518060
生物光学 多焦点结构光照明显微 亚衍射聚焦点阵 空间光调制器 相位恢复 bio-optics multifocal structured-illumination microscopy sub-diffraction spot array spatial light modulator phase retrieval 
2023, 50(15): 1507103
Author Affiliations
1 College of Physics and Optoelectronic Engineering, Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen 518060, Guangdong, P. R. China
2 Department of Bioengineering and COMSET, Clemson University, Clemson, SC 29634 USA
Structured illumination microscopy (SIM) is suitable for biological samples because of its relatively low-peak illumination intensity requirement and high imaging speed. The system resolution is affected by two typical detection modes: Point detection and area detection. However, a systematic analysis of the imaging performance of the different detection modes of the system has rarely been conducted. In this study, we compared laser point scanning point detection (PS-PD) and point scanning area detection (PS-AD) imaging in nonconfocal microscopy through theoretical analysis and simulated imaging. The results revealed that the imaging resolutions of PS-PD and PS-AD depend on excitation and emission point spread functions (PSFs), respectively. Especially, we combined the second harmonic generation (SHG) of point detection (P-SHG) and area detection (A-SHG) with SIM to realize a nonlinear SIM-imaging technique that improves the imaging resolution. Moreover, we analytically and experimentally compared the nonlinear SIM performance of P-SHG with that of A-SHG.
Super-resolution structured illumination microscopy second harmonic generation 
Journal of Innovative Optical Health Sciences
2023, 16(4): 2350010
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
雷云泽 1†郜鹏 1,**†刘星 1李娇月 1[ ... ]姚保利 2
1 西安电子科技大学物理学院,陕西 西安 710071
2 中国科学院西安光学精密机械研究所瞬态光学与光子技术国家重点实验室,陕西 西安 710119
成像系统 结构光照明显微 共振扫描 数字共聚焦显微 大深度成像 三维层析成像 imaging systems structured illumination microscopy resonant scanning digital confocal microscopy high penetration-depth imaging three-dimensional optical section imaging 
2023, 60(8): 0811016
Author Affiliations
1 Peking University, Institute of Molecular Medicine, College of Future Technology, Center for Life Sciences, State Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Beijing, China
2 Peking University, School of Software and Microelectronics, Beijing, China
3 Chongqing University of Posts and Telecommunications, College of Computer Science and Technology, Chongqing Key Laboratory of Image Cognition, Chongqing, China
4 Peking University, Biomedical Engineering Department, Beijing, China
5 Peking University, International Cancer Institute, Beijing, China
6 PKU-IDG/McGovern Institute for Brain Research, Beijing, China
7 Beijing Academy of Artificial Intelligence, Beijing, China
8 National Biomedical Imaging Center, Beijing, China

Structured illumination microscopy (SIM) has been widely used in live-cell superresolution (SR) imaging. However, conventional physical model-based SIM SR reconstruction algorithms are prone to artifacts in handling raw images with low signal-to-noise ratios (SNRs). Deep-learning (DL)-based methods can address this challenge but may lead to degradation and hallucinations. By combining the physical inversion model with a total deep variation (TDV) regularization, we propose a hybrid restoration method (TDV-SIM) that outperforms conventional or DL methods in suppressing artifacts and hallucinations while maintaining resolutions. We demonstrate the performance superiority of TDV-SIM in restoring actin filaments, endoplasmic reticulum, and mitochondrial cristae from extremely low SNR raw images. Thus TDV-SIM represents the ideal method for prolonged live-cell SR imaging with minimal exposure and photodamage. Overall, TDV-SIM proves the power of integrating model-based reconstruction methods with DL ones, possibly leading to the rapid exploration of similar strategies in high-fidelity reconstructions of other microscopy methods.

structured illumination microscopy superresolution reconstruction deep learning 
Advanced Photonics Nexus
2023, 2(1): 016012
周博 1王昆浩 2陈良怡 1,3,4,5,*
1 北京大学 未来技术学院 分子医学研究所, 北大-清华生命科学联合中心, 膜生物学国家重点实验室, 心脏代谢分子医学北京市重点实验室, 北京 100871
2 华南师范大学生物光子学院, 激光生命科学教育部重点实验室, 广东 广州 510631
3 北京大学IDG麦戈文脑科学研究所, 北京 100871
4 北京人工智能研究院, 北京 100871
5 国家生物医学成像科学中心, 北京 100871
作为现代超分辨成像技术的早期组成部分,结构照明显微镜(SIM)已经发展了近20年。其近期在活细胞中实现了高达60 nm和564 Hz的最佳时空分辨率组合,但也存在一些源于内在重建过程的缺点。本文综述了SIM技术的最新进展,包括超分辨率(SR)重建算法、性能评估及SIM与其他成像技术的集成,以便为生物学家提供实用指导。
结构光照明显微镜 超分辨率成像 structured illumination microscopy super-resolution imaging 
2022, 15(6): 1211
吉林大学 电子科学与工程学院 集成光电子学国家重点实验室, 吉林 长春 130012
脂滴是真核细胞中必不可少的一种球形细胞器,与很多细胞生理学过程息息相关。荧光成像技术是观察研究脂滴最有力的工具之一。受光学衍射极限的限制,传统的宽场以及共聚焦显微镜所能达到的成像分辨率约为250 nm左右,这对于观测小脂滴,尤其是新生脂滴(尺寸约30~60 nm)来说是远远不够的。在这种情况下,近年来新兴的各种能够打破衍射极限的超分辨荧光显微镜(如受激发射损耗显微镜、结构光照明显微镜以及光激活定位显微镜等)逐渐吸引了科研人员的兴趣。为了得到高分辨率脂滴荧光图像,除了上述超分辨显微镜之外,还需要具有与之相匹配的高性能荧光探针。本文将简要介绍这几种超分辨显微镜的工作原理,讨论其对荧光探针光物理性质的特殊要求,并进一步系统总结脂滴超分辨成像荧光探针的研究进展。与此同时,本文将分析对比不同超分辨显微镜在脂滴荧光成像方面的优势与不足,并对其发展趋势进行展望。
脂滴 超分辨成像 受激发射损耗显微镜 结构光照明显微镜 光激活定位显微镜 荧光探针 lipid droplets super-resolution imaging stimulated emission depletion microscopy structured illumination microscopy photoactivated localization microscopy fluorescent probes 
2022, 15(6): 1228
戴太强 1,2,3,4高晔 1,2,3,4马英 5蔡卜磊 1,2,3,4[ ... ]孔亮 1,2,3,4,*
1 军事口腔医学国家重点实验室,陕西 西安 710032
2 国家口腔疾病临床医学研究中心,陕西 西安 710032
3 陕西省口腔疾病临床医学研究中心,陕西 西安 710032
4 第四军医大学口腔医院 颌面外科,陕西 西安 710032
5 西安电子科技大学 物理学院,陕西 西安 710171
观察细胞器间动态相互作用,深入分析作用规律,对于揭示生理病理过程现象背后的机制具有十分重要的意义。传统光学显微镜受到由光波波长和孔径造成的衍射极限的限制,无法观测细胞器纳米级精细结构及细胞器间相互作用的动态变化规律。超分辨显微成像技术的出现为细胞器相互作用研究提供了重要手段,在深入揭示细胞器相互作用规律,阐明生理病理现象深层的机制研究中发挥了重要的作用。文中介绍了受激发射损耗(Stimulated emission depletion, STED)显微成像、结构光照明显微成像(Structured illumination microscopy, SIM)、单分子定位显微成像(Single molecule localization microscopy, SMLM)技术,并总结了这三类超分辨显微成像技术在细胞器相互作用中的应用与现状,为超分辨显微成像技术在细胞器相互作用研究中的应用提供思路拓展。最后,对超分辨显微成像技术在细胞器相互作用研究中的优势与不足进行分析总结,展望了超分辨显微成像技术在活细胞内细胞器相互作用成像中的需求发展趋势,为光学与医学及生物学的交叉融合发展提供一定的参考。
超分辨显微成像 细胞器间相互作用 受激发射损耗显微成像 结构光照明显微成像 单分子定位显微成像 super-resolution microscopy organelle interaction stimulated emission depletion microscopy structured illumination microscopy single molecule localization microscopy 
2022, 51(11): 20220622

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