Sinogram completion using a denoising diffusion probabilistic model for limited-angle reconstruction

This research primarily aims to address the reconstruction problem of limited-angle CT. In this work, we utilized a generative artificial intelligence model to complete the limited sinogram, resulting in a full sinogram that can be used for reconstructing medical images. During the sinogram completion process, we also applied the physical properties of the sinogram as constraints to enhance the precision of the completion.