Body fat compartment determination by encoder–decoder convolutional neural network: application to amyotrophic lateral sclerosis

The objective of this study was to automate the discrimination and quantification of human abdominal body fat compartments into subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) from T1-weighted MRI using encoder-decoder convolutional neural networks (CNN) and to apply the algorith...

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Detalles Bibliográficos
Autores principales: Vernikouskaya, Ina, Müller, Hans-Peter, Felbel, Dominik, Roselli, Francesco, Ludolph, Albert C., Kassubek, Jan, Rasche, Volker
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976026/
https://www.ncbi.nlm.nih.gov/pubmed/35365743
http://dx.doi.org/10.1038/s41598-022-09518-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976026/
https://www.ncbi.nlm.nih.gov/pubmed/35365743
http://dx.doi.org/10.1038/s41598-022-09518-w

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