A Combined Region- and Pixel-Based Deep Learning Approach for Quantifying Abdominal Adipose Tissue in Adolescents Using Dixon Magnetic Resonance Imaging

Background: The development of adipose tissue during adolescence may provide valuable insights into obesity-associated diseases. We propose an automated convolutional neural network (CNN) approach using Dixon-based magnetic resonance imaging (MRI) to quantity abdominal subcutaneous adipose tissue (S...

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Detalles Bibliográficos
Autores principales: Ogunleye, Olanrewaju A., Raviprakash, Harish, Simmons, Ashlee M., Bovell, Rhasaan T.M., Martinez, Pedro E., Yanovski, Jack A., Berman, Karen F., Schmidt, Peter J., Jones, Elizabeth C., Bagheri, Hadi, Biassou, Nadia M., Hsu, Li-Yueh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844424/
https://www.ncbi.nlm.nih.gov/pubmed/36648999
http://dx.doi.org/10.3390/tomography9010012

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844424/
https://www.ncbi.nlm.nih.gov/pubmed/36648999
http://dx.doi.org/10.3390/tomography9010012

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