Dose Prediction
Dose prediction, the automated estimation of radiation or therapeutic agent distribution, aims to optimize treatment efficacy and minimize adverse effects in various medical applications, primarily radiotherapy. Current research heavily utilizes deep learning, employing architectures like transformers, convolutional neural networks (CNNs), and diffusion models, often incorporating anatomical information and incorporating uncertainty quantification techniques like risk-controlling prediction sets. These advancements offer the potential to accelerate treatment planning, improve treatment precision, and enhance patient safety by providing more accurate and reliable dose estimations.
Papers
Latent Spaces Enable Transformer-Based Dose Prediction in Complex Radiotherapy Plans
Edward Wang, Ryan Au, Pencilla Lang, Sarah A. Mattonen
Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy
Paul Fischer, Hannah Willms, Moritz Schneider, Daniela Thorwarth, Michael Muehlebach, Christian F. Baumgartner