ArticleIEEE transactions on medical imaging2025
Physics-Informed Score-Based Diffusion Model for Limited-Angle Reconstruction of Cardiac Computed Tomography.
Article in IEEE transactions on medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Accelerated Physics-guided Diffusion Model for 3D Limited-angle Reconstruction of Cardiac Computed Tomography.IEEE transactions on radiation and plasma medical sciences · 2026Article
- Standardized Images and Evaluation Metrics for Tomography.Tomography (Ann Arbor, Mich.) · 2026Article
- Real-time volumetric CBCT reconstruction using surface and X-ray imaging for image-guided radiotherapy.Medical image analysis · 2025Article
- Multi-Material Decomposition Using Spectral Diffusion Posterior Sampling.IEEE transactions on bio-medical engineering · 2025Article
- Patch-based dual-domain photon-counting CT data correction with residual-based WGAN-ViT.Physics in medicine and biology · 2025Article
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Authors and funding
8 authors.
Funding
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.
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Registered trials
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