Jin Sung Kim

Reliability-weighted patch learning for synthetic CT reconstruction in head and neck adaptive radiotherapy: A proof-of-concept study.

BACKGROUND Cone-beam computed tomography (CBCT) is essential for adaptive radiotherapy (ART) but is limited by poor image quality. Existing deep learning methods for synthetic CT (sCT) generation face a critical trade-off: diffusion models offer high fidelity but are impractically slow, while fast-inference networks of...