Three-Dimensional Dose Prediction for Lung IMRT Patients with Deep Neural Networks: Robust Learning from Heterogeneous Beam Configurations. - Ana M. Barragan-Montero; Dan Nguyen; Weiguo Lu; Mu-Han Lin; Xavier Geets; Edmond Sterpin; Steve B. Jiang (CoRR, 2018)

Application of deep neural networks for automatic planning in radiation oncology treatments. - Ana M. Barragan-Montero; Dan Nguyen; Weiguo Lu; Mu-Han Lin; Xavier Geets; Edmond Sterpin; Steve B. Jiang (ESANN, 2019)

Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning. - Siri Willems; Wouter Crijns; Edmond Sterpin; Karin Haustermans; Frederik Maes (AIRT@MICCAI, 2019)

Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback. - Siri Willems; Heleen Bollen; Julie Van Der Veen; Edmond Sterpin; Wouter Crijns; Sandra Nuyts; Frederik Maes (CLIP/DCL/LL-COVID19/PPML@MICCAI, 2021)

Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers. - Sophie Wuyckens; Michael Saint-Guillain; Guillaume Janssens; Lewei Zhao; Xiaoqiang Li; Xuanfeng Ding; Edmond Sterpin; John A. Lee 001; Kevin Souris (Comput. Biol. Medicine, 2022)

PARROT - A Versatile Platform for AI-Driven Image Segmentation and Dose Prediction. - Wei Zhao; Margerie Huet-Dastarac; Sylvain Deffet; Edmond Sterpin; Ana M. Barragan-Montero; Sébastien Jodogne; John A. Lee 001 (MICAD, 2024)