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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Bibliographic Details

Published in:	Tomography
Main Authors:	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:	Article
Language:	English
Published:	MDPI AG 2023-01-01
Subjects:	abdominal adipose tissue magnetic resonance imaging fat quantification segmentation convolutional neural network
Online Access:	https://www.mdpi.com/2379-139X/9/1/12