  Cardiac computed tomography (CT) has emerged as a major imaging modality for
the diagnosis and monitoring of cardiovascular diseases. High temporal
resolution is essential to ensure diagnostic accuracy. Limited-angle data
acquisition can reduce scan time and improve temporal resolution, but typically
leads to severe image degradation and motivates for improved reconstruction
techniques. In this paper, we propose a novel physics-informed score-based
diffusion model (PSDM) for limited-angle reconstruction of cardiac CT. At the
sampling time, we combine a data prior from a diffusion model and a model prior
obtained via an iterative algorithm and Fourier fusion to further enhance the
image quality. Specifically, our approach integrates the primal-dual hybrid
gradient (PDHG) algorithm with score-based diffusion models, thereby enabling
us to reconstruct high-quality cardiac CT images from limited-angle data. The
numerical simulations and real data experiments confirm the effectiveness of
our proposed approach.
