Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning–based Denoising Image Filters

PURPOSE: To use deep learning to improve the image quality of subsampled images (number of acquisitions = 1 [NOA(1)]) to reduce whole-body diffusion-weighted MRI (WBDWI) acquisition times. MATERIALS AND METHODS: Both retrospective and prospective patient groups were used to develop a deep learning–b...

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Detalles Bibliográficos
Autores principales: Zormpas-Petridis, Konstantinos, Tunariu, Nina, Curcean, Andra, Messiou, Christina, Curcean, Sebastian, Collins, David J., Hughes, Julie C., Jamin, Yann, Koh, Dow-Mu, Blackledge, Matthew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Radiological Society of North America 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8489468/
https://www.ncbi.nlm.nih.gov/pubmed/34617028
http://dx.doi.org/10.1148/ryai.2021200279

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8489468/
https://www.ncbi.nlm.nih.gov/pubmed/34617028
http://dx.doi.org/10.1148/ryai.2021200279

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