mlsanityData to 7 Oct 2026

High-Frequency Space Diffusion Models for Accelerated MRI

arXiv 2208.05481 ↗First posted 10 Aug 2022eess.IV cs.CV cs.LGcited by 41

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Diffusion models with continuous stochastic differential equations (SDEs) have shown superior performances in image generation. It can serve as a deep generative prior to solving the inverse problem in magnetic resonance (MR) reconstruction. However, low-frequency regions of k-space data are typically fully sampled in fast MR imaging, while existing diffusion models are performed throughout the entire image or k-space, inevitably introducing uncertainty in the reconstruction of low-frequency regions. Additionally, existing diffusion models often demand substantial iterations to converge, resulting in time-consuming reconstructions. To address these challenges, we propose a novel SDE tailored specifically for MR reconstruction with the diffusion process in high-frequency space (referred to as HFS-SDE). This approach ensures determinism in the fully sampled low-frequency regions and accelerates the sampling procedure of reverse diffusion. Experiments conducted on the publicly available fastMRI dataset demonstrate that the proposed HFS-SDE method outperforms traditional parallel imaging methods, supervised deep learning, and existing diffusion models in terms of reconstruction accuracy and stability. The fast convergence properties are also confirmed through theoretical and experimental validation. Our code and weights are available at https://github.com/Aboriginer/HFS-SDE.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 26 of its 66 references that are in the map. First posted on arXiv 10 Aug 2022.

Builds on

26 of 66 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Adaptive Diffusion Priors for Accelerated MRI Reconstruction12 Jul
  2. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Models15 Nov
  3. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 23

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  6. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  7. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  8. 2018fastMRI: An Open Dataset and Benchmarks for Accelerated MRIcited by 464
  9. 2017MoDL: Model Based Deep Learning Architecture for Inverse Problemscited by 384
  10. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  11. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 284
  12. 2017A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstructioncited by 231
11 more
  1. 2020End-to-End Variational Networks for Accelerated MRI Reconstructioncited by 201
  2. 2022Diffusion Deformable Model for 4D Temporal Medical Image Generationcited by 65
  3. 2016On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integratorscited by 35
  4. 2020Unpaired Deep Learning for Accelerated MRI using Optimal Transport Driven CycleGANcited by 28
  5. 2022Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directionscited by 19
  6. 2021Deep Manifold Learning for Dynamic MR Imagingcited by 8
  7. 2022Self-supervised Deep Unrolled Reconstruction Using Regularization by Denoisingcited by 8
  8. 2022WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstructioncited by 8
  9. 2021Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRIcited by 5
  10. 2017On-the-fly Adaptive k-Space Sampling for Linear MRI Reconstruction Using Moment-Based Spectral Analysiscited by 3
  11. 2013Parallel Magnetic Resonance Imaging as Approximation in a Reproducing Kernel Hilbert Spacecited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 4; 2024: 19; 2025: 14; 2026: 2.

41 papers.

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  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  2. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  3. 2024Constrained Synthesis with Projected Diffusion Modelscited by 83
  4. 2024Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theorycited by 58
  5. 20243D MedDiffusion: A 3D Medical Latent Diffusion Model for Controllable and High-quality Medical Image Generationcited by 37
  6. 2024Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generationcited by 33
  7. 2024Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysiscited by 24
  8. 2025Training-Free Constrained Generation With Stable Diffusion Modelscited by 20
  9. 2023Learning Fourier-Constrained Diffusion Bridges for MRI Reconstructioncited by 13
  10. 2023SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRIcited by 12
  11. 2024Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstructioncited by 9
  12. 2025FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidancecited by 7
29 more
  1. 2025MRI Super-Resolution with Deep Learning: A Comprehensive Surveycited by 7
  2. 2025Diffusion Model Quantization: A Reviewcited by 6
  3. 2024Highly Accelerated MRI via Implicit Neural Representation Guided Posterior Sampling of Diffusion Modelscited by 5
  4. 2023Score-based Diffusion Models With Self-supervised Learning For Accelerated 3D Multi-contrast Cardiac Magnetic Resonance Imagingcited by 4
  5. 2024MRPD: Undersampled MRI reconstruction by prompting a large latent diffusion modelcited by 3
  6. 2024Score-based Generative Priors Guided Model-driven Network for MRI Reconstructioncited by 3
  7. 2025Exploring the latent space of diffusion models directly through singular value decompositioncited by 3
  8. 2024MCU-Net: A Multi-prior Collaborative Deep Unfolding Network with Gates-controlled Spatial Attention for Accelerated MR Image Reconstructioncited by 2
  9. 2024Diff-DTI: Fast Diffusion Tensor Imaging Using A Feature-Enhanced Joint Diffusion Modelcited by 2
  10. 2024Robust Simultaneous Multislice MRI Reconstruction Using Slice-Wise Learned Generative Diffusion Priorscited by 2
  11. 2024Diff-INR: Generative Regularization for Electrical Impedance Tomographycited by 2
  12. 2025Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Modelscited by 2
  13. 2024Accelerating MRI with Longitudinally-informed Latent Posterior Samplingcited by 1
  14. 2024Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstructioncited by 1
  15. 2025Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive Sensingcited by 1
  16. 2023Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Reviewcited by 0
  17. 2024The object detection method aids in image reconstruction evaluation and clinical interpretation of meniscal abnormalitiescited by 0
  18. 2024TC-KANRecon: High-Quality and Accelerated MRI Reconstruction via Adaptive KAN Mechanisms and Intelligent Feature Scalingcited by 0
  19. 2024MS-Glance: Bio-Insipred Non-semantic Context Vectors and their Applications in Supervising Image Reconstructioncited by 0
  20. 2024LDPM: Towards undersampled MRI reconstruction with MR-VAE and Latent Diffusion Priorcited by 0
  21. 2025Advancing MRI Reconstruction: A Systematic Review of Deep Learning and Compressed Sensing Integrationcited by 0
  22. 2025Low-Rank Augmented Implicit Neural Representation for Unsupervised High-Dimensional Quantitative MRI Reconstructioncited by 0
  23. 2025Diffusion-Assisted Frequency Attention Model for Whole-body Low-field MRI Reconstructioncited by 0
  24. 2025Diffusion Models for Solving Inverse Problems via Posterior Sampling with Piecewise Guidancecited by 0
  25. 2025MID: A Self-supervised Multimodal Iterative Denoising Frameworkcited by 0
  26. 2025Reconstructing Multi-Scale Physical Fields from Extremely Sparse Measurements with an Autoencoder-Diffusion Cascadecited by 0
  27. 2025FLAT: FLow-Aligned Training of Unrolled Networks for MRI Reconstructioncited by 0
  28. 2026Variational Network with Wavelet-based UNET in Accelerated MRI Reconstruction from Under Sampled K-space Datacited by 0
  29. 2026Self-Auditing Residual Drifting for Pathology-Preserving Accelerated Knee MRIcited by 0

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  1. 2023Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models
  2. 2023Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstruction
  3. 2026High-dimensional Embedding Prior for Noisy K-space Domain MRIReconstruction
  4. 2023Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstruction
  5. 2023Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noise
  6. 2024Autoregressive Image Diffusion: Generation of Image Sequence and Application in MRI
  7. 2022Towards performant and reliable undersampled MR reconstruction via diffusion model sampling
  8. 2025MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers