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Incorporating Prior Knowledge via Volumetric Deep Residual Network to Optimize the Reconstruction of Sparsely Sampled MRI
For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via deep learning and utilized for image reconstructio...
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| Publicado no: | Magn Reson Imaging |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6745016/ https://ncbi.nlm.nih.gov/pubmed/30880112 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.mri.2019.03.012 |
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