Adaptive radiotherapy dose prediction on head and neck cancer patients with a 3D multi-headed U-Net deep learning architecture

作者：H. Wang, Austen Maniscalco, David J. Sher, Mu-Han Lin, Steve Jiang, Dan Nguyen · 发表于：Machine Learning Health · 年份：2025 · DOI：10.1088/3049-477x/adfade · 被引用次数：2 · 研究领域：Advanced Radiotherapy Techniques、Lung Cancer Diagnosis and Treatment、Medical Imaging Techniques and Applications

< 0.05). Taken together, these findings demonstrate that the proposed MHU-Met advances DL-based dose prediction for ART by effectively integrating both pre-treatment and adaptive session data. This approach facilitates the generation of dose distributions that more closely resemble the clinical ground truth, supporting personalization in ART planning and improving alignment with physician intent and treatment objectives.