System and method for metal artifact reduction in medical images using a denoising diffusion probabilistic model

An imaging system comprising:

• a memory configured to store instructions;
• and
• one or more processors configured to execute the instructions to perform operations comprising:
• acquiring a corrupted computed tomography (CT) image, of a region of interest (ROI) of a subject, including artifacts caused by a metal object in the subject;
• generating a corrupted sinogram, corresponding to the corrupted CT image, including a corrupted region of corrupted data caused by the metal object and an uncorrupted region of uncorrupted data;
• generating a mask sinogram that delineates the corrupted region of the corrupted data;
• generating a corrected sinogram including the uncorrupted region of the uncorrupted data and an inpainted region of inpainted data corresponding to the corrupted region, using a denoising diffusion probabilistic model (DDPM), the corrupted sinogram, and the mask sinogram;
• generating a corrected CT image, of the ROI of the subject, that includes reduced artifacts relative to the artifacts in the corrupted CT image, based on the corrected sinogram;
• and
• displaying the corrected CT image.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of an imaging system, cause the one or more processors to perform operations comprising:

• acquiring a corrupted computed tomography (CT) image, of a region of interest (ROI) of a subject, including artifacts caused by a metal object in the subject;
• generating a corrupted sinogram, corresponding to the corrupted CT image, including a corrupted region of corrupted data caused by the metal object and an uncorrupted region of uncorrupted data;
• generating a mask sinogram that delineates the corrupted region of the corrupted data;
• generating a corrected sinogram including the uncorrupted region of the uncorrupted data and an inpainted region of inpainted data corresponding to the corrupted region, using a denoising diffusion probabilistic model (DDPM), the corrupted sinogram, and the mask sinogram;
• generating a corrected CT image, of the ROI of the subject, that includes reduced artifacts relative to the artifacts in the corrupted CT image, based on the corrected sinogram;
• and
• displaying the corrected CT image.