Abstract: Intracranial aneurysm embolization, oral metal implants, spinal internal fixation, hip replacement, and other metal implants are increasingly used in clinical practice. Metal artifacts generated by computed tomography (CT) images during the evaluation of patients after placement of metal implants will prevent CT images from clearly showing the metal–bone interface and the adjacent tissue structure, which affects the accuracy of doctors' diagnosis. With the development of CT, metal artifact reduction technology and virtual monoenergetic imaging technology are helpful to reduce metal artifacts in CT imaging. The emergence of deep learning reconstruction algorithms and photon counting CT provides a more reliable basis for the accurate evaluation of metal implants after surgery. This paper reviews the progress of research on reducing metal artifacts in CT imaging.