The POP-AART Lab centers its research on one core theme: online adaptive radiation therapy.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
Computer Vision
With a commitment to explainable systems.
The POP-AART Lab is dedicated to developing AI technology which involves deep learning and covers fundamental research topics within radiotherapy.
The lab’s mission and vision are to focus on the use of artificial intelligence for precision radiotherapy.
The impact of the lab lies in developing novel AI strategies for improving the images on which the radiation treatment is based, predicting changes over time of the tumor and incorporating them in automatic treatment planning and adaptation.
Deep Generative Learning for Cone Beam Computed Tomography: Goal: to design deep generative models that improve CBCT image quality while enforcing geometric and pathological integrity.
Learning Inverse Models for Cone Beam Computed Tomography Reconstruction: Goal: to learn deep inverse models to infer high quality 3D and 4D CBCT from measured projections that optimally exploit the existing knowledge from the physical acquisition processes
Deep Learning Geometry for 3D Medical Image Registration: Goal: to learn models that optimally register the varying geometries in pairs or series of images of deformable anatomy
Interactive Deep Learning for Medical Segmentation: Goal: to replace static segmentation models with interactive model based approaches that can, therefore, integrate the feedback provided by the experts interactively and can minimise or eliminate even violations of the constrains are necessary
Learning to Forecast for Adaptive Radiation Therapy: Goal: to learn forecasting models that predict dose distributions for a given anatomy and series of future anatomies and associated dose distributions in adaptive radiation treatment
Reinforcement Learning for Radiation Treatment Plan optimisation: Goal: to improve and accelerate treatment plan optimization using novel reinforcement learning algorithms for guiding radiation in adaptive radiotherapy treatment
Elekta, headquartered in Stockholm, Sweden, is a leader in precision radiation medicine with more than 4,000 employees worldwide.
Netherlands Cancer Institute is among the top 10 comprehensive cancer centres, combining world-class fundamental, translational, and clinical research with dedicated patient care.
University of Amsterdam (UvA) is the Netherlands’ largest university, offering the widest range of academic programmes.
