7 citations · 9 across the 3 of their papers we have counts for
3 papers
One scale to rule them all: interpretable multi-scale Deep Learning for predicting cell survival after proton and carbon ion irradiation
Giulio Bordieri, Giorgio Cartechini, Anna Bianchi +4
The relationship between the physical characteristics of the radiation field and biological damage is central to both radiotherapy and radioprotection, yet the link between spatial…
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…
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…