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Mitigating transmit‐B(1) artifacts by predicting parallel transmission images with deep learning: A feasibility study using high‐resolution whole‐brain diffusion at 7 Tesla

PURPOSE: To propose a novel deep learning (DL) approach to transmit‐B(1) (B(1) (+))‐artifact mitigation without direct use of parallel transmission (pTx), by predicting pTx images from single‐channel transmission (sTx) images. METHODS: A deep encoder–decoder convolutional neural network was construc...

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Detalles Bibliográficos
Autores principales:	Ma, Xiaodong, Uğurbil, Kâmil, Wu, Xiaoping
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2022
Materias:	Research Articles–Imaging Methodology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324974/ https://www.ncbi.nlm.nih.gov/pubmed/35403237 http://dx.doi.org/10.1002/mrm.29238

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