Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation Article Swipe
YOU?
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· 2023
· Open Access
·
· DOI: https://doi.org/10.1038/s41377-023-01321-0
In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead to misconceptions. Current mapping methods fail to finely estimate the local quality, challenging to associate the SR scale content. Here, we develop a rolling Fourier ring correlation (rFRC) method to evaluate the reconstruction uncertainties down to SR scale. To visually pinpoint regions with low reliability, a filtered rFRC is combined with a modified resolution-scaled error map (RSM), offering a comprehensive and concise map for further examination. We demonstrate their performances on various SR imaging modalities, and the resulting quantitative maps enable better SR images integrated from different reconstructions. Overall, we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41377-023-01321-0
- https://www.nature.com/articles/s41377-023-01321-0.pdf
- OA Status
- gold
- Cited By
- 47
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389738284
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4389738284Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41377-023-01321-0Digital Object Identifier
- Title
-
Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-14Full publication date if available
- Authors
-
Weisong Zhao, Xiaoshuai Huang, Jianyu Yang, Liying Qu, Guo‐Hua Qiu, Yue Zhao, Xinwei Wang, Deer Su, Xumin Ding, Heng Mao, Yaming Jiu, Ying Hu, Jiubin Tan, Shiqun Zhao, Leiting Pan, Liangyi Chen, Haoyu LiList of authors in order
- Landing page
-
https://doi.org/10.1038/s41377-023-01321-0Publisher landing page
- PDF URL
-
https://www.nature.com/articles/s41377-023-01321-0.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.nature.com/articles/s41377-023-01321-0.pdfDirect OA link when available
- Concepts
-
Resolution (logic), Computer science, Reliability (semiconductor), Scale (ratio), Image quality, Fourier transform, Artificial intelligence, Noise (video), Microscopy, Computer vision, Pattern recognition (psychology), Image (mathematics), Mathematics, Optics, Geography, Cartography, Physics, Quantum mechanics, Mathematical analysis, Power (physics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
47Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 24, 2024: 20, 2023: 3Per-year citation counts (last 5 years)
- References (count)
-
58Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5100358564 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 17 |
| corresponding_institution_ids | https://openalex.org/I204983213 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.99338588 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |