Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography

TL;DR

This paper introduces a physics-informed score-based diffusion model that combines data and model priors to improve limited-angle cardiac CT reconstruction, achieving high-quality images from reduced scan data.

Contribution

The novel integration of a diffusion model with an iterative Fourier fusion and PDHG algorithm enhances limited-angle cardiac CT reconstruction quality.

Findings

Effective reconstruction from limited-angle data demonstrated in simulations.

Improved image quality over traditional methods shown in real data experiments.

The approach reduces scan time while maintaining diagnostic image quality.

Abstract

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.