mlsanityData to 7 Oct 2026

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

arXiv 2405.14770 ↗First posted 23 May 2024eess.IVcited by 10

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 21 of its 46 references that are in the map. First posted on arXiv 23 May 2024.

Builds on

21 of 46 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Solving 3D Inverse Problems using Pre-trained 2D Diffusion Models19 Nov
  2. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Models15 Nov
  3. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 18

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  3. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  4. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  5. 2022Classifier-Free Diffusion Guidancecited by 5,717
  6. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  7. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  8. 2022Diffusion Posterior Sampling for General Noisy Inverse Problemscited by 1,375
  9. 2019An Introduction to Variational Autoencoderscited by 997
  10. 2022Denoising Diffusion Restoration Modelscited by 951
  11. 2017Towards Principled Methods for Training Generative Adversarial Networkscited by 460
  12. 2016Deep Convolutional Neural Network for Inverse Problems in Imagingcited by 431
6 more
  1. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  2. 2023Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistencycited by 180
  3. 2014Playing with Duality: An Overview of Recent Primal-Dual Approaches for Solving Large-Scale Optimization Problemscited by 25
  4. 2019TomoGAN: Low-Dose Synchrotron X-Ray Tomography with Generative Adversarial Networkscited by 25
  5. 2019Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimatorscited by 4
  6. 2023Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosiscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 4.

10 papers.

  1. 2025Dynamics-aware Diffusion Models for Planning and Controlcited by 4
  2. 2025Autoregressive regularized score-based diffusion models for multi-scenarios fluid flow predictioncited by 2
  3. 2026Generative Drifting for Conditional Medical Image Generationcited by 2
  4. 2025Limited-Angle CBCT Reconstruction via Geometry-Integrated Cycle-domain Denoising Diffusion Probabilistic Modelscited by 1
  5. 2025ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstructioncited by 0
  6. 2025Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentationcited by 0
  7. 2025Limited-Angle Tomography Reconstruction via Projector Guided 3D Diffusioncited by 0
  8. 2026Continuity-driven Synergistic Diffusion with Neural Priors for Ultra-Sparse-View CBCT Reconstructioncited by 0
  9. 2026Limited-Angle CT Reconstruction Using Multi-Volume Latent Consistency Modelcited by 0
  10. 2026Physics-Embedded Feature Learning for AI in Medical Imagingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025PWD: Prior-Guided and Wavelet-Enhanced Diffusion Model for Limited-Angle CT
  2. 2025Clinical Metadata Guided Limited-Angle CT Image Reconstruction
  3. 2023CT Reconstruction using Diffusion Posterior Sampling conditioned on a Nonlinear Measurement Model
  4. 2023Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT
  5. 2024RN-SDEs: Limited-Angle CT Reconstruction with Residual Null-Space Diffusion Stochastic Differential Equations
  6. 2025Advancing Limited-Angle CT Reconstruction Through Diffusion-Based Sinogram Completion
  7. 2022DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction
  8. 2024DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction