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…
k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
Moritz Rempe, Florian Mentzel, Kelsey L. Pomykala +5
Objectives: Present a novel deep learning-based skull stripping algorithm for magnetic resonance imaging (MRI) that works directly in the information rich k-space. Materials and Me…
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…