3 papers
physics.med-ph2026
A Fast and Generic Energy-Shifting Transformer for Hybrid Monte Carlo Radiotherapy Calculation
Chi-Hieu Pham, Didier Benoit, Vincent Bourbonne +3
We introduce a novel learning framework for accelerated Monte Carlo (MC) dose calculation termed Energy-Shifting. This approach leverages deep learning to synthesize highly complex…
physics.med-ph2026
Machine Learning-Based Modeling of the Anode Heel Effect in X-ray Beam Monte Carlo Simulations
Hussein Harb, Didier Benoit, Axel Rannou +4
To develop a machine learning-based framework for accurately modeling the anode heel effect in Monte Carlo simulations of X-ray imaging systems, enabling realistic beam intensity p…
physics.med-ph2025
Deep Learning-Based Beamlet Model for Generic X-Ray Beam Dose Calculation
Maxime Rousselot, Jing Zhang, Didier Benoit +2
Modeling the absorbed dose during X-ray imaging is essential for optimizing radiation exposure. Monte Carlo simulations (MCS) are the gold standard for precise 3D dose estimation b…