Multi‐sequence MR image‐based synthetic CT generation using a generative adversarial network for head and neck MRI‐only radiotherapy

Purpose The purpose of this study is to investigate the effect of different magnetic resonance (MR) sequences on the accuracy of deep learning‐based synthetic computed tomography (sCT) generation in the complex head and neck region. Methods Four sequences of MR images (T1, T2, T1C, and T1DixonC‐water) were collected from 45 patients with nasopharyngeal carcinoma. Seven conditional generative adversarial network (cGAN) models were trained with...