3 citations · 3 across the 8 of their papers we have counts for
8 papers
Direct probabilistic IMPT treatment planning with setup and range errors for neuro-oncological patients
Jelte R. de Jong, Sebastiaan Breedveld, Steven J. M. Habraken +4
To show clinical feasibility of a previously proposed probabilistic planning approach that can precisely optimize for clinical goals with patient-specific acceptance probabilities…
A Deep Learning-based surrogate model for Severe Accidents in nuclear reactors using ASTEC
Alessandro Longhi, Danny Lathouwers, Zoltán Perkó
Integral codes like the Accident Source Term Evaluation Code (ASTEC) are powerful tools to study the physics of Severe Accidents (SAs) in nuclear reactors. Real time SA simulators…
Angle dependent dose transformer algorithm for fast proton therapy dose calculations
Mikołaj Stryja, Danny Lathouwers, Zoltán Perkó
Accurate 3D dose calculation for Pencil Beam Scanning Proton Therapy (PBSPT) is typically performed with Monte Carlo (MC) engines, but their runtimes limit adaptive workflows and r…
Probabilistic Proton Treatment Planning: a novel approach for optimizing underdosage and overdosage probabilities of target and organ structures
Jelte R. de Jong, Sebastiaan Breedveld, Steven J. M. Habraken +3
Treatment planning uncertainties are typically managed using margin-based or robust optimization. Margin-based methods expand the clinical target volume (CTV) to a planning target…
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs
Alessandro Longhi, Danny Lathouwers, Zoltán Perkó
Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their…
A Deterministic Dynamical Low-rank Approach for Charged Particle Transport
Pia Stammer, Tiberiu Burlacu, Niklas Wahl +2
Deterministically solving charged particle transport problems at a sufficient spatial and angular resolution is often prohibitively expensive, especially due to their highly forwar…
A deep learning model for inter-fraction head and neck anatomical changes
Tiberiu Burlacu, Mischa Hoogeman, Danny Lathouwers +1
Objective: To assess the performance of a probabilistic deep learning based algorithm for predicting inter-fraction anatomical changes in head and neck patients. Approach: A probab…
Yet anOther Dose Algorithm (YODA) for independent computations of dose and dose changes due to anatomical changes
Tiberiu Burlacu, Danny Lathouwers, Zoltán Perkó
To assess the viability of a physics-based, deterministic and adjoint-capable algorithm for performing treatment planning system independent dose calculations a…