Simulation Data-Based Dual Domain Network (Sim-DDNet) for Motion Artifact Reduction in MR Images
Brain magnetic resonance imaging (MRI) is highly susceptible to motion artifacts that degrade fine structural details and undermine quantitative analysis. Conventional U-Net-based deep learning approaches for motion artifact reduction typically operate only in the image domain and are often trained...
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| Hlavní autoři: | , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI AG
2026-01-01
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| Edice: | Magnetochemistry |
| Témata: | |
| On-line přístup: | https://www.mdpi.com/2312-7481/12/1/14 |
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