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Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy
Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming p...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10173768/ https://www.ncbi.nlm.nih.gov/pubmed/37181226 http://dx.doi.org/10.1016/j.xinn.2023.100425 |
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author | Wang, Zhaojun Zhao, Tianyu Cai, Yanan Zhang, Jingxiang Hao, Huiwen Liang, Yansheng Wang, Shaowei Sun, Yujie Chen, Tongsheng Bianco, Piero R. Oh, Kwangsung Lei, Ming |
author_facet | Wang, Zhaojun Zhao, Tianyu Cai, Yanan Zhang, Jingxiang Hao, Huiwen Liang, Yansheng Wang, Shaowei Sun, Yujie Chen, Tongsheng Bianco, Piero R. Oh, Kwangsung Lei, Ming |
author_sort | Wang, Zhaojun |
collection | PubMed |
description | Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories. |
format | Online Article Text |
id | pubmed-10173768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101737682023-05-12 Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy Wang, Zhaojun Zhao, Tianyu Cai, Yanan Zhang, Jingxiang Hao, Huiwen Liang, Yansheng Wang, Shaowei Sun, Yujie Chen, Tongsheng Bianco, Piero R. Oh, Kwangsung Lei, Ming Innovation (Camb) Article Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories. Elsevier 2023-04-13 /pmc/articles/PMC10173768/ /pubmed/37181226 http://dx.doi.org/10.1016/j.xinn.2023.100425 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Wang, Zhaojun Zhao, Tianyu Cai, Yanan Zhang, Jingxiang Hao, Huiwen Liang, Yansheng Wang, Shaowei Sun, Yujie Chen, Tongsheng Bianco, Piero R. Oh, Kwangsung Lei, Ming Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title | Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title_full | Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title_fullStr | Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title_full_unstemmed | Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title_short | Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
title_sort | rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10173768/ https://www.ncbi.nlm.nih.gov/pubmed/37181226 http://dx.doi.org/10.1016/j.xinn.2023.100425 |
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