• PhotoniX
  • Vol. 4, Issue 1, 19 (2023)
Gang Wen1、2, Simin Li3, Yong Liang2, Linbo Wang2, Jie Zhang2, Xiaohu Chen2, Xin Jin2, Chong Chen2, Yuguo Tang1、2、*, and Hui Li2、**
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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    DOI: 10.1186/s43074-023-00092-6 Cite this Article
    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 Copy Citation Text show less

    Abstract

    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.
    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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