Accelerating error correction in tomographic reconstruction
Recent advances in scanning probe-based tomographic imaging have greatly improved spatial resolution, but systematic and random errors are a serious impediment to reliable data extraction. Here, a combined optimization and alignment algorithm provides a scalable approach to error-correcting reconstr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-07-01
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| Series: | Communications Materials |
| Online Access: | https://doi.org/10.1038/s43246-022-00267-x |
| Summary: | Recent advances in scanning probe-based tomographic imaging have greatly improved spatial resolution, but systematic and random errors are a serious impediment to reliable data extraction. Here, a combined optimization and alignment algorithm provides a scalable approach to error-correcting reconstruction of large datasets. |
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| ISSN: | 2662-4443 |