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| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.05677 |
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| _version_ | 1866910144234782720 |
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| author | Wang, Mengrui Shu, Manming Yan, Jiajing Liu, Chang Fu, Xiangda Zhang, Jingxiang Lin, Yuchen Zhao, Hu Huang, Yuwei Ma, Dingbang Ge, Yifan Hao, Huiwen Zhao, Tianyu Liang, Yansheng Wang, Shaowei Lei, Ming |
| author_facet | Wang, Mengrui Shu, Manming Yan, Jiajing Liu, Chang Fu, Xiangda Zhang, Jingxiang Lin, Yuchen Zhao, Hu Huang, Yuwei Ma, Dingbang Ge, Yifan Hao, Huiwen Zhao, Tianyu Liang, Yansheng Wang, Shaowei Lei, Ming |
| contents | Three-dimensional (3D) fluorescence imaging provides a vital approach for study of biological tissues with intricate structures, and optical sectioning structured illumination microscopy (OS-SIM) stands out for its high imaging speed, low phototoxicity and high spatial resolution. However, OS-SIM faces the problem of low signal-to-noise ratio (SNR) when using traditional decoding algorithms, especially in thick tissues. Here we propose a Hilbert-transform decoding and space domain based high-low (HT-SHiLo) algorithm for noise suppression in OS-SIM. We demonstrate HT-SHiLo algorithm can significantly improve the SNR of optical sectioning images at rapid processing speed, and double the imaging depth in thick tissues. With our OS-SIM system, we achieve high quality 3D images of various biological samples including mouse brains, Drosophila clock neurons, organoids, and live cells. We anticipate that this approach will render OS-SIM a powerful technique for research of cellular organelles or thick tissues in 3D morphology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_05677 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | High SNR 3D Imaging from Millimeter-scale Thick Tissues to Cellular Dynamics via Structured Illumination Microscopy Wang, Mengrui Shu, Manming Yan, Jiajing Liu, Chang Fu, Xiangda Zhang, Jingxiang Lin, Yuchen Zhao, Hu Huang, Yuwei Ma, Dingbang Ge, Yifan Hao, Huiwen Zhao, Tianyu Liang, Yansheng Wang, Shaowei Lei, Ming Optics Three-dimensional (3D) fluorescence imaging provides a vital approach for study of biological tissues with intricate structures, and optical sectioning structured illumination microscopy (OS-SIM) stands out for its high imaging speed, low phototoxicity and high spatial resolution. However, OS-SIM faces the problem of low signal-to-noise ratio (SNR) when using traditional decoding algorithms, especially in thick tissues. Here we propose a Hilbert-transform decoding and space domain based high-low (HT-SHiLo) algorithm for noise suppression in OS-SIM. We demonstrate HT-SHiLo algorithm can significantly improve the SNR of optical sectioning images at rapid processing speed, and double the imaging depth in thick tissues. With our OS-SIM system, we achieve high quality 3D images of various biological samples including mouse brains, Drosophila clock neurons, organoids, and live cells. We anticipate that this approach will render OS-SIM a powerful technique for research of cellular organelles or thick tissues in 3D morphology. |
| title | High SNR 3D Imaging from Millimeter-scale Thick Tissues to Cellular Dynamics via Structured Illumination Microscopy |
| topic | Optics |
| url | https://arxiv.org/abs/2412.05677 |