PhotoniX, Volume. 4, Issue 1, 19(2023)

Spectrum-optimized direct image reconstruction of super-resolution structured illumination microscopy

Gang Wen1...2, Simin Li3, Yong Liang2, Linbo Wang2, Jie Zhang2, Xiaohu Chen2, Xin Jin2, Chong Chen2, Yuguo Tang1,2,* and Hui Li2,** |Show fewer author(s)
Author Affiliations
  • 1Academy for Engineering and Technology, Fudan University, Shanghai 200433, China
  • 2Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163 Jiangsu, China
  • 3College of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan 250014, China
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    Super-resolution structured illumination microscopy (SR-SIM) has become a widely used nanoscopy technique for rapid, long-term, and multi-color imaging of live cells. Precise but troublesome determination of the illumination pattern parameters is a prerequisite for Wiener-deconvolution-based SR-SIM image reconstruction. Here, we present a direct reconstruction SIM algorithm (direct-SIM) with an initial spatial-domain reconstruction followed by frequency-domain spectrum optimization. Without any prior knowledge of illumination patterns and bypassing the artifact-sensitive Wiener deconvolution procedures, resolution-doubled SR images could be reconstructed by direct-SIM free of common artifacts, even for the raw images with large pattern variance in the field of view (FOV). Direct-SIM can be applied to previously difficult scenarios such as very sparse samples, periodic samples, very small FOV imaging, and stitched large FOV imaging.

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    Gang Wen, Simin Li, Yong Liang, Linbo Wang, Jie Zhang, Xiaohu Chen, Xin Jin, Chong Chen, Yuguo Tang, Hui Li. Spectrum-optimized direct image reconstruction of super-resolution structured illumination microscopy[J]. PhotoniX, 2023, 4(1): 19

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    Paper Information

    Category: Research Articles

    Received: Dec. 22, 2022

    Accepted: Apr. 21, 2023

    Published Online: Jul. 10, 2023

    The Author Email: Tang Yuguo (tangyg@sibet.ac.cn), Li Hui (hui.li@sibet.ac.cn)

    DOI:10.1186/s43074-023-00092-6

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