3 papers
physics.med-ph2026
Overcoming data scarcity through multi-center federated learning for organs-at-risk segmentation in pediatric upper abdominal radiotherapy
Mianyong Ding, Maximilian Knoll, Semi Harrabi +7
Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy workflows, but models trained on adult data often underperform in pediatric pati…
cs.CV2025
Automated segmentation of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023
M. A. D. Buser, D. C. Simons, M. Fitski +27
Surgery plays an important role within the treatment for neuroblastoma, a common pediatric cancer. This requires careful planning, often via magnetic resonance imaging (MRI)-based…
eess.IV2024
Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy
Mianyong Ding, Matteo Maspero, Annemieke S Littooij +5
Purposes: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatric upper abdominal tumors and…