Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes

OBJECTIVE: To accurately estimate liver PDFF from chemical shift-encoded (CSE) MRI using a deep learning (DL)-based Multi-Decoder Water-Fat separation Network (MDWF-Net), that operates over complex-valued CSE-MR images with only 3 echoes. METHODS: The proposed MDWF-Net and a U-Net model were indepen...

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Detalles Bibliográficos
Autores principales: Meneses, Juan Pablo, Arrieta, Cristobal, della Maggiora, Gabriel, Besa, Cecilia, Urbina, Jesús, Arrese, Marco, Gana, Juan Cristóbal, Galgani, Jose E., Tejos, Cristian, Uribe, Sergio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415440/
https://www.ncbi.nlm.nih.gov/pubmed/37014405
http://dx.doi.org/10.1007/s00330-023-09576-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415440/
https://www.ncbi.nlm.nih.gov/pubmed/37014405
http://dx.doi.org/10.1007/s00330-023-09576-2

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