Deep Learning-Based 4D Dual-Energy CBCT Generation for Material Decomposition
To propose a deep-learning approach for predicting high from low-energy 4D-CBCT.
Poster Program · Therapy Physics
Author profile
Laboratory Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142 China
To propose a deep-learning approach for predicting high from low-energy 4D-CBCT.
To propose and validate a novel dosimetric method integrating inter-fractional temporal dose changes for improved SCLC prognosis management and individualized decision-making.