7 citations · 9 across the 3 of their papers we have counts for
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physics.med-ph2025★ 2 cited
Machine Learning-based beam delivery time model for Mevion 250i with Hyperscan technology
Giorgio Cartechini, Francesco Giuseppe Cordoni, Mirko Unipan +1
Purpose: Accurate prediction of beam delivery time (BDT) is essential for operational efficiency, 4D dose calculations, and advanced proton therapy techniques. Despite its importan…
physics.med-ph2023★ 7 cited
Integrating microdosimetric in vitro RBE models for particle therapy into TOPAS MC using the MicrOdosimetry-based modeling for RBE Assessment (MONAS) tool
Giorgio Cartechini, Marta Missiaggia, Emanuele Scifoni +2
We present MONAS (MicrOdosimetry-based modelliNg for relative biological effectiveness (RBE) ASsessment) toolkit. MONAS is a TOPAS Monte Carlo extension, that combines simulations…