Cone beam CT based validation of neural network generated synthetic CTs for radiotherapy in the head region

Purpose In the past years, many different neural network‐based conversion techniques for synthesizing computed tomographys (sCTs) from MR images have been published. While the model's performance can be checked during the training against the test set, test datasets can never represent the whole population. Conversion errors can still occur for special cases, for example, for unusual anatomical situations. Therefore, the performance of sCT...