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DEEP NEURAL NETWORK (DNN) FOR WATER/FAT SEPARATION: SUPERVISED TRAINING, UNSUPERVISED TRAINING, AND NO TRAINING
PURPOSE: To use a deep neural network (DNN) for solving the optimization problem of water/fat separation and to compare supervised and unsupervised training. METHODS: The current T2*-IDEAL algorithm for solving water/fat separation is dependent on initialization. Recently, DNN has been proposed to s...
Gorde:
| Argitaratua izan da: | Magn Reson Med |
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| Egile Nagusiak: | , , , , , , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2020
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7809709/ https://ncbi.nlm.nih.gov/pubmed/33107127 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mrm.28546 |
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