most citedFast and accurate dose predictions for novel radiotherapy treatments in heterogeneous phantoms using conditional 3D-UNet generative adversarial networks

26 citations · 27 across the 2 of their papers we have counts for

collaborators

2 papers

physics.med-ph2022★ 1 cited

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…

physics.med-ph2022★ 26 cited

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…