A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography ; volume:15 ; number:1 ; day:23 ; month:9 ; year:2024 ; pages:1-12 ; date:12.2024
Nature Communications ; 15, Heft 1 (23.9.2024), 1-12, 12.2024
- Creator
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Wiedemann, Simon
Heckel, Reinhard
- Contributor
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SpringerLink (Online service)
- DOI
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10.1038/s41467-024-51438-y
- URN
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urn:nbn:de:101:1-2412092109143.214225536084
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:25 AM CEST
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Associated
- Wiedemann, Simon
- Heckel, Reinhard
- SpringerLink (Online service)
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Simultaneous Denoising and Heterogeneity Learning for Time Series Data
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Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
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Two-stage strategy using denoising autoencoders for robust reference-free genotype imputation with missing input genotypes
Deflectometry and image denoising
A Cryogenic Testbed for Polarization Modulators and Cryogenic Mechanisms
Reduzierung von Missing-Wedge-Artefakten mit DIRECTT
Simultaneous Denoising and Heterogeneity Learning for Time Series Data
Artifacts denoising of EEG acquired during simultaneous EEG-FMRI
Image Denoising
Denoising stacked autoencoders for transient electromagnetic signal denoising
A denoising stacked autoencoders for transient electromagnetic signal denoising
Photogrammetric DSM denoising
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
Two-stage strategy using denoising autoencoders for robust reference-free genotype imputation with missing input genotypes
Deflectometry and image denoising