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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主要な著者:	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
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2023-01-01
シリーズ:	Tomography
主題:	abdominal adipose tissue magnetic resonance imaging fat quantification segmentation convolutional neural network
オンライン･アクセス:	https://www.mdpi.com/2379-139X/9/1/12
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