5 papers
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…
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…
Semi-Supervised Learning for Dose Prediction in Targeted Radionuclide: A Synthetic Data Study
Jing Zhang, Alexandre Bousse, Chi-Hieu Pham +2
Targeted Radionuclide Therapy (TRT) is a modern strategy in radiation oncology that aims to administer a potent radiation dose specifically to cancer cells using cancer-targeting r…
GATE 10 Monte Carlo particle transport simulation -- Part I: development and new features
David Sarrut, Nicolas Arbor, Thomas Baudier +30
We present GATE version 10, a major evolution of the open-source Monte Carlo simulation application for medical physics, built on Geant4. This release marks a transformative evolut…
GATE 10 Monte Carlo particle transport simulation -- Part II: architecture and innovations
Nils Krah, Nicolas Arbor, Thomas Baudier +29
Over the past years, we have developed GATE version 10, a major re-implementation of the long-standing Geant4-based Monte Carlo application for particle and radiation transport sim…