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20242026
most citedA Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs

3 citations · 3 across the 8 of their papers we have counts for

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5 papers · 1 filter

physics.med-ph2026

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…

physics.med-ph2026

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…

physics.med-ph2025

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…

physics.med-ph2024

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…

physics.med-ph2024

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…