351 citations · 1.1k across the 24 of their papers we have counts for
25 papers
Toward High-Resolution Detection of Target Fragmentation: TEA-Sensitized NIT for Proton Therapy Applications
V. Boccia, T. Asada, A. Alexandrov +96
Nano Imaging Trackers (NIT) are fine-grained nuclear emulsions capable of tracking charged particles with sub-micrometric spatial resolution. The DAMON (Direct Measurement of Targe…
Measurement of 80-200 MeV/n O nuclear cross-section on Carbon and Polyethylene targets with the nuclear emulsion detector of the FOOT experiment
FOOT Collaboration, Giuliana Galati, Vincenzo Boccia +93
Accurate knowledge of nuclear fragmentation cross-sections is essential for optimizing charged particle therapy. In this study, conducted within the framework of the FOOT (Fragment…
Cross Section Measurements of Large Angle Fragments Production in the Interaction of Carbon Ion Beams with Thin Targets
The FOOT Collaboration, Y. Dong, I. Mattei +87
The fragmentation cross sections of carbon ion beams with kinetic energies of impinging on thin targets of graphite (C), polyvinyl-toluene (CH)…
Angular differential and elemental fragmentation cross sections of a beam on a graphite target with the FOOT experiment
FOOT Collaboration, R. Ridolfi, M. Toppi +88
This paper presents the measurements of the angular differential cross sections for the forward production of He, Li, Be, B, C and N nuclei in the fragmentation process of a 400$\t…
Analysis methods for in-beam PET images in proton therapy treatment verification: a comparison based on Monte Carlo simulations
M. Moglioni, A. C. Kraan, A. Berti +13
Background and purpose: In-beam Positron Emission Tomography (PET) is one of the modalities that can be used for in-vivo non-invasive treatment monitoring in proton therapy. PET di…
Analysis of time-profiles with in-beam PET monitoring in charged particle therapy
A. C. Kraan, S. Muraro, G. Battistoni +14
Background: Treatment verification with PET imaging in charged particle therapy is conventionally done by comparing measurements of spatial distributions with Monte Carlo (MC) pred…