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https://open.uns.ac.rs/handle/123456789/6539
Title: | Estimation of subcutaneous and visceral fat tissue volume on abdominal MR images | Authors: | Spasojević A. Stojanov, Oliver Lončar-Turukalo, Tatjana Šveljo, Olivera |
Issue Date: | 1-Jan-2015 | Journal: | 12th Symposium on Neural Network Applications in Electrical Engineering, NEUREL 2014 - Proceedings | Abstract: | © 2014 IEEE. Fat depots at different location are associated with variable metabolic risks. It has been noted that visceral abdominal adipose tissue contributes more to these risks than subcutaneous adipose tissue. For discrimination between subcutaneous and visceral adipose tissue contemporary studies primarily use cross sectional medical imaging. Fat volume at different anatomical locations is usually identified and determined either manually or in semiautomatic manner. In this study we combined different image processing methods for unsupervised discrimination of subcutaneous and visceral adipose tissue on abdominal T1 MR images. Procedure has been tested on 16 subjects and results are compared with visceral and subcutaneous volume obtained by semiautomatic method from the literature. High correlation was achieved for subcutaneous fat tissue volume (0.98) while for visceral fat tissue good correlation has been noted (0.86). | URI: | https://open.uns.ac.rs/handle/123456789/6539 | ISBN: | 9781479958887 | DOI: | 10.1109/NEUREL.2014.7011511 |
Appears in Collections: | FTN Publikacije/Publications |
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