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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...

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Detalhes bibliográficos
Publicado no:Magn Reson Med
Main Authors: Jafari, Ramin, Spincemaille, Pascal, Zhang, Jinwei, Nguyen, Thanh D., Luo, Xianfu, Cho, Junghun, Margolis, Daniel, Prince, Martin R., Wang, Yi
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
Assuntos:
Acesso em linha: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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