The invention discloses a DDPM-based CT image
metal artifact
elimination method, and aims to solve the artifact problem caused by a
metal object in an existing CT image and improve
image quality and diagnosis reliability. A
diffusion model of unconditional training is adopted, step-by-step
back diffusion repair of an artifact area is carried out in a sinogram domain, an unrepaired area is dynamically adjusted by combining with a
metal mask, accurate repair of the artifact area is achieved, and
original data of the area which is not affected by artifacts are kept. In the training stage of the
system, artifact-free data are gradually converted into standard
Gaussian noise through forward
diffusion; in the
inference stage, data are gradually recovered by utilizing
back diffusion, block repair is carried out on an artifact region by combining with a metal
mask, and a complete sinogram is generated through region merging. And finally, reconstructing a CT image by using a filtered
back projection algorithm, and optimizing boundary transition through a
smoothing algorithm to ensure seamless connection between the metal object and surrounding tissues.