activity
20212024
most citedA Unified Generation-Registration Framework for Improved MR-based CT Synthesis in Proton Therapy

3 citations · 7 across the 5 of their papers we have counts for

collaborators

6 papers

physics.med-ph2024★ 1 cited

GAMBAS -- Fast Beam Arrangement Selection for Proton Therapy using a Nearest Neighbour Model

Renato Bellotti, Nicola Bizzocchi, Antony J. Lomax +3

Purpose: Beam angle selection is critical in proton therapy treatment planning, yet automated approaches remain underexplored. This study presents and evaluates GAMBAS, a novel, fa…

physics.med-ph2024★ 1 cited

JulianA.jl -- A Julia package for radiotherapy

Renato Bellotti, Antony J. Lomax, Andreas Adelmann +1

The importance of computers is continually increasing in radiotherapy. Efficient algorithms, implementations and the ability to leverage advancements in computer science are crucia…

physics.med-ph2024

Clinical utility of automatic treatment planning for proton therapy of head-and-neck cancer patients using JulianA

Renato Bellotti, Alexey Cherchik, Jonas Willmann +3

Background: Automatic treatment planning promises many benefits for both research and clinical environments. For clinics, autoplanning promises to reduce planning time and achieve…

physics.med-ph2024★ 3 cited

A Unified Generation-Registration Framework for Improved MR-based CT Synthesis in Proton Therapy

Xia Li, Renato Bellotti, Barbara Bachtiary +5

Background: In MR-guided proton therapy planning, aligning MR and CT images is key for MR-based CT synthesis, especially in mobile regions like the head-and-neck. Misalignments her…

physics.med-ph2023★ 2 cited

JulianA: An automatic treatment planning platform for intensity-modulated proton therapy and its application to intra- and extracerebral neoplasms

Renato Bellotti, Jonas Willmann, Antony J. Lomax +3

Creating high quality treatment plans is crucial for a successful radiotherapy treatment. However, it demands substantial effort and special training for dosimetrists. Existing aut…

physics.acc-ph2021

Fast, efficient and flexible particle accelerator optimisation using densely connected and invertible neural networks

Renato Bellotti, Romana Boiger, Andreas Adelmann

Particle accelerators are enabling tools for scientific exploration and discovery in various disciplines. Finding optimized operation points for these complex machines is a challen…