mlsanityData to 7 Oct 2026

Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction

arXiv 2209.00835 ↗First posted 2 Sep 2022eess.IV cs.CVcited by 23

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Recently, score-based diffusion models have shown satisfactory performance in MRI reconstruction. Most of these methods require a large amount of fully sampled MRI data as a training set, which, sometimes, is difficult to acquire in practice. This paper proposes a fully-sampled-data-free score-based diffusion model for MRI reconstruction, which learns the fully sampled MR image prior in a self-supervised manner on undersampled data. Specifically, we first infer the fully sampled MR image distribution from the undersampled data by Bayesian deep learning, then perturb the data distribution and approximate their probability density gradient by training a score function. Leveraging the learned score function as a prior, we can reconstruct the MR image by performing conditioned Langevin Markov chain Monte Carlo (MCMC) sampling. Experiments on the public dataset show that the proposed method outperforms existing self-supervised MRI reconstruction methods and achieves comparable performances with the conventional (fully sampled data trained) score-based diffusion methods.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 16 of its 37 references that are in the map. First posted on arXiv 2 Sep 2022.

Builds on

16 of 37 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 15

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  6. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  7. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 526
  8. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 284
  9. 2017Image reconstruction by domain transform manifold learningcited by 231
  10. 2019Noisier2Noise: Learning to Denoise from Unpaired Noisy Datacited by 125
  11. 2020Deep Low-rank plus Sparse Network for Dynamic MR Imagingcited by 32
  12. 2019LORAKI: Autocalibrated Recurrent Neural Networks for Autoregressive MRI Reconstruction in k-Spacecited by 27
3 more
  1. 2019Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Datacited by 17
  2. 2021Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancementcited by 17
  3. 2021Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRIcited by 5

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Cited by year

Citing papers per year: 2022: 3; 2023: 13; 2024: 5; 2025: 2.

23 papers.

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  1. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  2. 2022A Survey on Generative Diffusion Modelcited by 238
  3. 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Datacited by 108
  4. 2023Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Datacited by 40
  5. 2024Efficient Diffusion Models: A Comprehensive Survey from Principles to Practicescited by 39
  6. 2023Self-Supervised MRI Reconstruction with Unrolled Diffusion Modelscited by 37
  7. 2024Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Datacited by 32
  8. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  9. 2023Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoisingcited by 15
  10. 2023Learning Fourier-Constrained Diffusion Bridges for MRI Reconstructioncited by 13
  11. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  12. 2022Deep unfolding as iterative regularization for imaging inverse problemscited by 5
11 more
  1. 2024Highly Accelerated MRI via Implicit Neural Representation Guided Posterior Sampling of Diffusion Modelscited by 5
  2. 2023Score-based Diffusion Models With Self-supervised Learning For Accelerated 3D Multi-contrast Cardiac Magnetic Resonance Imagingcited by 4
  3. 2023Joint Supervised and Self-supervised Learning for MRI Reconstructioncited by 4
  4. 2024Robust multi-coil MRI reconstruction via self-supervised denoisingcited by 4
  5. 2024Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR Imagingcited by 4
  6. 2023Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusioncited by 2
  7. 2023Poisson-Gaussian Holographic Phase Retrieval with Score-based Image Priorcited by 1
  8. 2023JSMoCo: Joint Coil Sensitivity and Motion Correction in Parallel MRI with a Self-Calibrating Score-Based Diffusion Modelcited by 1
  9. 2025Re-Visible Dual-Domain Self-Supervised Deep Unfolding Network for MRI Reconstructioncited by 1
  10. 2023Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN samplercited by 0
  11. 2025Dual-domain Multi-path Self-supervised Diffusion Model for Accelerated MRI Reconstructioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Measurement Score-Based Diffusion Model
  2. 2025Measurement Score-Based MRI Reconstruction with Automatic Coil Sensitivity Estimation
  3. 2025A Self-supervised Diffusion Bridge for MRI Reconstruction
  4. 2025Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data
  5. 2024MRPD: Undersampled MRI reconstruction by prompting a large latent diffusion model
  6. 2022Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction
  7. 2024Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
  8. 2022Bayesian MRI Reconstruction with Joint Uncertainty Estimation using Diffusion Models