• 저자Chang Min Hyun,Jin Keun Seo,Sung Min Lee,박형석,전기완
• 학술지Medical Physics (0094-2405), 49, 5195 ~ 5205
• 등재유형SCIE
• 게재일자 20220518

Dental cone-beam computed tomography (CBCT) has been increasingly used for dental and maxillofacial imaging. However, the presence of metallic inserts, such as implants, crowns, and dental braces, violates the CT model assumption, which leads to severe metal artifacts in the reconstructed CBCT image, resulting in the degradation of diagnostic performance. In this study,we used deep learning to reduce metal artifacts.