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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
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 |
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Professor Geoffrey Dixon
Publicado: (1980) -
Allan Dixon Mitchell
Publicado: (1913)