CBCT‐based synthetic CT generation using deep‐attention cycleGAN for pancreatic adaptive radiotherapy

Purpose Current clinical application of cone‐beam CT (CBCT) is limited to patient setup. Imaging artifacts and Hounsfield unit (HU) inaccuracy make the process of CBCT‐based adaptive planning presently impractical. In this study, we developed a deep‐learning‐based approach to improve CBCT image quality and HU accuracy for potential extended clinical use in CBCT‐guided pancreatic adaptive radiotherapy. Methods Thirty patients previously treated...