26 citations · 49 across the 6 of their papers we have counts for
4 papers · 1 filter
Accurate and fast deep learning dose prediction for a preclinical microbeam radiation therapy study using low-statistics Monte Carlo simulations
Florian Mentzel, Jason Paino, Micah Barnes +13
Microbeam radiation therapy (MRT) utilizes coplanar synchrotron radiation beamlets and is a proposed treatment approach for several tumour diagnoses that currently have poor clinic…
A step towards treatment planning for microbeam radiation therapy: fast peak and valley dose predictions with 3D U-Nets
Florian Mentzel, Micah Barnes, Kevin Kröninger +9
Fast and accurate dose predictions are one of the bottlenecks in treatment planning for microbeam radiation therapy (MRT). In this paper, we propose a machine learning (ML) model b…
Fast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D-UNet generative adversarial networks
Florian Mentzel, Kevin Kröninger, Michael Lerch +8
Novel radiotherapy techniques like synchrotron X-ray microbeam radiation therapy (MRT), require fast dose distribution predictions that are accurate at the sub-mm level, especially…
No more glowing in the dark: How deep learning improves exposure date estimation in thermoluminescence dosimetry
Florian Mentzel, Evelin Derugin, Hannah Jansen +4
The time- or temperature-resolved detector signal from a thermoluminescence dosimeter can reveal additional information about circumstances of an exposure to ionizing irradiation.…