Federated learning on 310 CT scans from two centers yields pediatric OAR segmentation models with better cross-center robustness than local models for nine evaluated structures.
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Overcoming data scarcity through multi-center federated learning for organs-at-risk segmentation in pediatric upper abdominal radiotherapy
Federated learning on 310 CT scans from two centers yields pediatric OAR segmentation models with better cross-center robustness than local models for nine evaluated structures.