2 citations · 3 across the 6 of their papers we have counts for
6 papers
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…
CT respiratory motion synthesis using joint supervised and adversarial learning
Yi-Heng Cao, Vincent Bourbonne, François Lucia +4
Objective: Four-dimensional computed tomography (4DCT) imaging consists in reconstructing a CT acquisition into multiple phases to track internal organ and tumor motion. It is comm…
Fast-Track of F-18 Positron paths simulations using GANs
Youness Mellak, Konstantinos Chatzipapas, Alexandre Bousse +3
In recent years, the use of Monte Carlo (MC) simulations in the domain of Medical Physics has become a state-of-the-art technology that consumes lots of computational resources for…
On-line Dose Calculation Using Deep Learning for Beams Selection in Non-Coplanar Radiotherapy
Fang Guo, Franklin Okoli, Ulrike Schick +3
Non-coplanar Intensity-Modulated Radiation Therapy (IMRT) goes a step further by orienting the gantry carrying the radiation beam and the patient couch in a non-coplanar manner to…
Cross-modal tumor segmentation using generative blending augmentation and self training
Guillaume Sallé, Pierre-Henri Conze, Julien Bert +3
\textit{Objectives}: Data scarcity and domain shifts lead to biased training sets that do not accurately represent deployment conditions. A related practical problem is cross-modal…
Regularized directional representations for medical image registration
Vincent Jaouen, Pierre-Henri Conze, Guillaume Dardenne +2
In image registration, many efforts have been devoted to the development of alternatives to the popular normalized mutual information criterion. Concurrently to these efforts, an i…