72 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- KTH Royal Institute of TechnologySE13 papers
- Iridium KankernetwerkBE2 papers
- University of AntwerpBE2 papers
- Brigham and Women's HospitalUS1 paper
- Dana-Farber Brigham Cancer CenterUS1 paper
- Dana-Farber Cancer InstituteUS1 paper
- Harvard UniversityUS1 paper
- Institute of Information and Communication TechnologiesBG1 paper
- Ion Beam Applications (Belgium)BE1 paper
- KU LeuvenBE1 paper
- UCLouvainBE1 paper
- Uppsala UniversitySE1 paper
13 papers · 1 filter
Partitioning of multiple brain metastases improves dose gradients in single-isocenter radiosurgery
Johan Sundström, Anton Finnson, Elin Hynning +2
Background: A growing number of cancer patients with brain metastases can benefit from stereotactic radiosurgery (SRS) thanks to recent advances in systemic therapies. With an incr…
Shoot-through layers in upright proton arcs unlock advantages in plan quality and range verification
Erik Engwall, Victor Mikhalev, Johan Sundström +2
Background: Upright proton therapy with compact delivery systems has the potential to reduce costs for treatments but could also lead to broadening of the beam penumbra due to ener…
Efficient proton arc optimization and delivery through energy layer pre-selection and post-filtering
S. Wuyckens, V. Wase, O. Marthin +7
Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional…
Implications of Clinical Target Distribution Weighted Radiotherapy Optimization
Ivar Bengtsson, Anders Forsgren, Albin Fredriksson
Delineating and planning with respect to regions suspected to contain microscopic tumor cells is an inherently uncertain task in radiotherapy. The recently proposed \textit{clinica…
Robust automated radiation therapy treatment planning using scenario-specific dose prediction and robust dose mimicking
Oskar Eriksson, Tianfang Zhang
Purpose: We present a framework for robust automated treatment planning using machine learning, comprising scenario-specific dose prediction and robust dose mimicking. Methods: The…
Probabilistic Pareto plan generation for semiautomated multicriteria radiation therapy treatment planning
Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
Objective: We propose a semiautomatic pipeline for radiation therapy treatment planning, combining ideas from machine learning-automated planning and multicriteria optimization (MC…
Direct optimization of dose-volume histogram metrics in radiation therapy treatment planning
Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
We present a method of directly optimizing on deviations in clinical goal values in radiation therapy treatment planning. Using a new mathematical framework in which metrics derive…
Probabilistic feature extraction, dose statistic prediction and dose mimicking for automated radiation therapy treatment planning
Tianfang Zhang, Rasmus Bokrantz, Jimmy Olsson
Purpose: We propose a general framework for quantifying predictive uncertainties of dose-related quantities and leveraging this information in a dose mimicking problem in the conte…
Probabilistic dose prediction using mixture density networks for automated radiation therapy treatment planning
Viktor Nilsson, Hanna Gruselius, Tianfang Zhang +2
We demonstrate the application of mixture density networks (MDNs) in the context of automated radiation therapy treatment planning. It is shown that an MDN can produce good predict…
On Adaptation Cost and Tractability in Robust Adaptive Radiation Therapy Optimization
Michelle Böck
A framework for online robust adaptive radiation therapy (ART) is presented. This framework is designed to (i) handle interfractional geometric variations following a probability d…
On the Interplay between Robustness and Dynamic Planning for Adaptive Radiation Therapy
Michelle Böck, Kjell Eriksson, Anders Forsgren
Interfractional geometric uncertainties can lead to deviations of the actual delivered dose from the prescribed dose distribution. To better handle these uncertainties during treat…
Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning
Lovisa Engberg, Kjell Eriksson, Anders Forsgren +1
Conventional planning objectives in optimization of intensity-modulated radiotherapy treatment (IMRT) plans are designed to minimize the violation of dose-volume histogram (DVH) th…
The scenario-based generalization of radiation therapy margins
Albin Fredriksson, Rasmus Bokrantz
We give a scenario-based treatment plan optimization formulation that is equivalent to planning with geometric margins if the scenario doses are calculated using the static dose cl…