A projection‐domain correction method in CBCT reconstruction for head and neck radiotherapy using cycle‐GAN and nonlocal means filter

Background In radiation treatments for head and neck tumors, cone‐beam computed tomography (CBCT) is employed for patient positioning and dose calculation of adaptive radiotherapy. However, the quality of CBCT is degraded by the scatter and noise, majorly impacting the accuracy of patient positioning and dose calculation. Purpose To improve the quality of CBCT for patients with head and neck cancer, a projection‐domain CBCT correction method was proposed using a cycle‐consistent generative adversarial network (cycle‐GAN) and a nonlocal means filter (NLMF) based on a reference digitally reconstructed radiograph (DRR). Methods A cycle‐GAN was initially trained to learn mapping from CBCT projections to a DRR using the data obtained from 30 patients. For each patient, 671 CBCT projections were measured for CBCT reconstruction. Moreover, 360 Digital Reconstructed Radiographs (DRR) were computed from each patient's planning computed tomography (CT), whose projection angles ranged from 0° to 359° with an interval of 1°. By applying the trained generator of the cycle‐GAN to the unseen CBCT projection, a synthetic DRR with considerably less scatter was obtained. However, annular artifacts were observed in the CBCT reconstructed with synthetic DRR. To address this issue, a NLMF based on reference DRR was used to further correct the synthetic DRR, which corrected the synthetic DRR using the calculated DRR as a reference image. Finally, the CBCT with no annular artifact and little noise was reconstructed with the corrected synthetic DRR. The proposed method was tested using the data of six patients. The corrected synthetic DRR and CBCT were compared with the corresponding real DRR and CT images. The structural preservation ability of the proposed method was evaluated using the Dice coefficients of the automatically extracted nasal cavity. Moreover, the image quality of CBCT corrected with the proposed method was objectively assessed with an five‐point human scoring system and compared with CT, original CBCT and CBCT corrected with other strategies. Results The mean absolute value (MAE) of the relative error between the corrected synthetic and real DRR was