Search Results for author:
Found 5 papers, 2 papers with code
Multi-Task Learning for Integrated Automated Contouring and Voxel-Based Dose Prediction in Radiotherapy
Moreover in deep learning (DL), the contouring and dose prediction tasks for automated treatment planning are done independently.
Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications
Multi-task learning (MTL) is a powerful approach in deep learning that leverages the information from multiple tasks during training to improve model performance.
Domain Adaptation of Automated Treatment Planning from Computed Tomography to Magnetic Resonance
Significance: We were able to create highly acceptable MR based treatment plans using a CT-trained ML model for treatment planning, although clinically significant dose deviations from the CT based plans were observed.
OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines
The dose predictions were input to four optimization models to form 76 unique KBP pipelines that generated 7600 plans.
OpenKBP: The open-access knowledge-based planning grand challenge
The purpose of this work is to advance fair and consistent comparisons of dose prediction methods for knowledge-based planning (KBP) in radiation therapy research.
