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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Bibliografiske detaljer

Principais autores:	Olanrewaju A. Ogunleye, Harish Raviprakash, Ashlee M. Simmons, Rhasaan T.M. Bovell, Pedro E. Martinez, Jack A. Yanovski, Karen F. Berman, Peter J. Schmidt, Elizabeth C. Jones, Hadi Bagheri, Nadia M. Biassou, Li-Yueh Hsu
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2023-01-01
Serier:	Tomography
Fag:	abdominal adipose tissue magnetic resonance imaging fat quantification segmentation convolutional neural network
Online adgang:	https://www.mdpi.com/2379-139X/9/1/12
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