Abdominal fat quantification using convolutional networks

OBJECTIVES: To present software for automated adipose tissue quantification of abdominal magnetic resonance imaging (MRI) data using fully convolutional networks (FCN) and to evaluate its overall performance—accuracy, reliability, processing effort, and time—in comparison with an interactive referen...

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Detalles Bibliográficos
Autores principales: Schneider, Daniel, Eggebrecht, Tobias, Linder, Anna, Linder, Nicolas, Schaudinn, Alexander, Blüher, Matthias, Denecke, Timm, Busse, Harald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Gastrointestinal
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667157/
https://www.ncbi.nlm.nih.gov/pubmed/37436508
http://dx.doi.org/10.1007/s00330-023-09865-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667157/
https://www.ncbi.nlm.nih.gov/pubmed/37436508
http://dx.doi.org/10.1007/s00330-023-09865-w

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