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SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning
High resolution magnetic resonance (MR) images are desired in many clinical and research applications. Acquiring such images with high signal-to-noise (SNR), however, can require a long scan duration, which is difficult for patient comfort, is more costly, and makes the images susceptible to motion...
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| Veröffentlicht in: | IEEE Trans Med Imaging |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8053388/ https://ncbi.nlm.nih.gov/pubmed/33170776 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2020.3037187 |
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