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Self-Supervised Learning of Physics-Guided Reconstruction Neural Networks without Fully-Sampled Reference Data
PURPOSE: To develop a strategy for training a physics-guided MRI reconstruction neural network without a database of fully-sampled datasets. THEORY AND METHODS: Self-supervised learning via data under-sampling (SSDU) for physics-guided deep learning (DL) reconstruction partitions available measureme...
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| Published in: | Magn Reson Med |
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| Main Authors: | , , , , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7811359/ https://ncbi.nlm.nih.gov/pubmed/32614100 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mrm.28378 |
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