- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource, 1 online resource.
- Language
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Englisch
- Bibliographic citation
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Comparison of deep learning-based denoising methods in cardiac SPECT ; volume:10 ; number:1 ; day:8 ; month:2 ; year:2023 ; pages:1-15 ; date:12.2023
EJNMMI Physics ; 10, Heft 1 (8.2.2023), 1-15, 12.2023
- Creator
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Sohlberg, Antti
Kangasmaa, Tuija
Constable, Chris
Tikkakoski, Antti
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s40658-023-00531-0
- URN
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urn:nbn:de:101:1-2023082021011589772028
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:56 AM CEST
Data provider
This object is provided by:
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Sohlberg, Antti
- Kangasmaa, Tuija
- Constable, Chris
- Tikkakoski, Antti
- SpringerLink (Online service)
Other Objects (12)
Correction: Comparison of deep learning-based denoising methods in cardiac SPECT
Deep learning-based multi-frequency denoising for myocardial perfusion SPECT
Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
A survey on deep learning-based Monte Carlo denoising
Deep learning-based PET image denoising and reconstruction: a review
IMD-Net: A deep learning-based icosahedral mesh denoising network
Learning-based low-rank denoising
Correction to: Deep learning-based PET image denoising and reconstruction: a review
A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging
Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance
Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies
Deep learning-based methods for image reconstruction in cardiac CT and cardiac cine MRI
Correction: Comparison of deep learning-based denoising methods in cardiac SPECT
Deep learning-based multi-frequency denoising for myocardial perfusion SPECT
Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
A survey on deep learning-based Monte Carlo denoising
Deep learning-based PET image denoising and reconstruction: a review
IMD-Net: A deep learning-based icosahedral mesh denoising network
Learning-based low-rank denoising
Correction to: Deep learning-based PET image denoising and reconstruction: a review
A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging
Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance
Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies
Deep learning-based methods for image reconstruction in cardiac CT and cardiac cine MRI
Correction: Comparison of deep learning-based denoising methods in cardiac SPECT
Deep learning-based multi-frequency denoising for myocardial perfusion SPECT
Deep learning–based denoising of low-dose SPECT myocardial perfusion images: quantitative assessment and clinical performance
A survey on deep learning-based Monte Carlo denoising
Deep learning-based PET image denoising and reconstruction: a review
IMD-Net: A deep learning-based icosahedral mesh denoising network
Learning-based low-rank denoising
Correction to: Deep learning-based PET image denoising and reconstruction: a review
A deep learning-based automated diagnosis system for SPECT myocardial perfusion imaging
Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance
Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies