@article{be9e338496b04d0cb2bfec955c9b4810,
title = "Cross-cohort federated learning for pediatric abdominal adipose tissue segmentation and quantification using free-breathing 3D MRI",
keywords = "adipose tissue, federated learning, magnetic resonance imaging, pediatric obesity, segmentation",
author = "Wenwen Zhang and Kafali, \{Sevgi Gokce\} and Timothy Adamos and Kelsey Kuwahara and Ashley Dong and Jessica Li and Shih, \{Shu Fu\} and Timoteo Delgado-Esbenshade and Shilpy Chowdhury and Spencer Loong and Jeremy Moretz and Barnes, \{Samuel R.\} and Zhaoping Li and Shahnaz Ghahremani and Calkins, \{Kara L.\} and Wu, \{Holden H.\}",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2026. Published by Oxford University Press on behalf of the Radiological Society of North America. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact
[email protected] for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site{\textemdash}for further information please contact
[email protected].",
year = "2026",
month = jan,
doi = "10.1093/radadv/umag002",
language = "English",
volume = "3",
journal = "Radiology Advances",
issn = "2976-9337",
number = "1",
}