mlsanityData to 7 Oct 2026

DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models

arXiv 2302.03018 ↗First posted 6 Feb 2023eess.IV cs.CVcited by 50

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique. However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting in increased costs and patient discomfort, and decreased throughput. Thus, there is great interest in denoising MRI scans, especially for the subtype of diffusion MRI scans that are severely SNR-limited. While most prior MRI denoising methods are supervised in nature, acquiring supervised training datasets for the multitude of anatomies, MRI scanners, and scan parameters proves impractical. Here, we propose Denoising Diffusion Models for Denoising Diffusion MRI (DDM2), a self-supervised denoising method for MRI denoising using diffusion denoising generative models. Our three-stage framework integrates statistic-based denoising theory into diffusion models and performs denoising through conditional generation. During inference, we represent input noisy measurements as a sample from an intermediate posterior distribution within the diffusion Markov chain. We conduct experiments on 4 real-world in-vivo diffusion MRI datasets and show that our DDM2 demonstrates superior denoising performances ascertained with clinically-relevant visual qualitative and quantitative metrics.

Key facts. Cited by 50 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 33 of its 56 references that are in the map. First posted on arXiv 6 Feb 2023.

Builds on

33 of 56 references.

Closest ancestors · 2

Same direction, newest first

  1. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Models15 Nov
  2. 2020Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning2 Nov

Other references · 31

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  7. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  8. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  9. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  10. 2017Deep Image Priorcited by 1,097
  11. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 734
  12. 2020WaveGrad: Estimating Gradients for Waveform Generationcited by 620
19 more
  1. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 526
  2. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  3. 2022GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generationcited by 511
  4. 2018Noise2Void - Learning Denoising from Single Noisy Imagescited by 359
  5. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  6. 2019Noise2Self: Blind Denoising by Self-Supervisioncited by 274
  7. 2022Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Qualitycited by 181
  8. 2021Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Imagescited by 171
  9. 2019High-Quality Self-Supervised Deep Image Denoisingcited by 161
  10. 2021Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Imagescited by 110
  11. 2020Solving Linear Inverse Problems Using the Prior Implicit in a Denoisercited by 78
  12. 2022MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusioncited by 66
  13. 2022BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesiscited by 64
  14. 2021Measuring Robustness in Deep Learning Based Compressive Sensingcited by 53
  15. 2018Unsupervised Learning with Stein's Unbiased Risk Estimatorcited by 47
  16. 2022SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluationcited by 42
  17. 2021VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstructioncited by 16
  18. 2020Accelerating Prostate Diffusion Weighted MRI using Guided Denoising Convolutional Neural Network: Retrospective Feasibility Studycited by 5
  19. 2021Noise2Recon: Enabling Joint MRI Reconstruction and Denoising with Semi-Supervised and Self-Supervised Learningcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 20; 2025: 14; 2026: 5.

50 papers.

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  1. 2023Generative AI for Medical Imaging: extending the MONAI Frameworkcited by 68
  2. 2024Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Datacited by 44
  3. 2023Solving Inverse Problems with Score-Based Generative Priors learned from Noisy Datacited by 40
  4. 2023GSURE-Based Diffusion Model Training with Corrupted Datacited by 40
  5. 2024Efficient Diffusion Models: A Comprehensive Survey from Principles to Practicescited by 39
  6. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  7. 2023Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstructioncited by 14
  8. 2023Learning Fourier-Constrained Diffusion Bridges for MRI Reconstructioncited by 13
  9. 2024Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Surveycited by 11
  10. 2024Replication in Visual Diffusion Models: A Survey and Outlookcited by 11
  11. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  12. 2024MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applicationscited by 7
38 more
  1. 2025Measurement Score-Based Diffusion Modelcited by 7
  2. 2025MRI Super-Resolution with Deep Learning: A Comprehensive Surveycited by 7
  3. 2024When Diffusion MRI Meets Diffusion Model: A Novel Deep Generative Model for Diffusion MRI Generationcited by 6
  4. 2025Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinementcited by 6
  5. 2025Score-based Self-supervised MRI Denoisingcited by 6
  6. 2023Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encodingcited by 5
  7. 2024PFCM: Poisson flow consistency models for low-dose CT image denoisingcited by 4
  8. 2024Field-of-View Extension for Brain Diffusion MRI via Deep Generative Modelscited by 4
  9. 2024RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Modelscited by 4
  10. 2024Robust multi-coil MRI reconstruction via self-supervised denoisingcited by 4
  11. 2024Volumetric Conditioning Module to Control Pretrained Diffusion Models for 3D Medical Imagescited by 3
  12. 2025DiffDenoise: Self-Supervised Medical Image Denoising with Conditional Diffusion Modelscited by 3
  13. 2026Improving 2D Diffusion Models for 3D Medical Imaging with Inter-Slice Consistent Stochasticitycited by 3
  14. 2023A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRIcited by 2
  15. 2024White Matter Geometry-Guided Score-Based Diffusion Model for Tissue Microstructure Imputation in Tractography Imagingcited by 2
  16. 2023Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and Generalizabilitycited by 1
  17. 2023DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic Modelscited by 1
  18. 2024Visual Privacy Auditing with Diffusion Modelscited by 1
  19. 2024Iterative Learning for Joint Image Denoising and Motion Artifact Correction of 3D Brain MRIcited by 1
  20. 2024QID2: An Image-Conditioned Diffusion Model for Q-space Up-sampling of DWI Datacited by 1
  21. 2024Multi-Modality Conditioned Variational U-Net for Field-of-View Extension in Brain Diffusion MRIcited by 1
  22. 2024Equivariant spatio-hemispherical networks for diffusion MRI deconvolutioncited by 1
  23. 2025MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classificationcited by 1
  24. 2025Score-based Diffusion Model for Unpaired Virtual Histology Stainingcited by 1
  25. 2025MAN: Latent Diffusion Enhanced Multistage Anti-Noise Network for Efficient and High-Quality Low-Dose CT Image Denoisingcited by 1
  26. 2025USB: Unified Synthetic Brain Framework for Bidirectional Pathology-Healthy Generation and Editingcited by 1
  27. 2026Unsupervised Denoising of Diffusion-Weighted Images with Bias and Variance Corrected Noise Modelingcited by 1
  28. 2024Investigating Self-Supervised Image Denoising with Denaturationcited by 0
  29. 2024Reliable Deep Diffusion Tensor Estimation: Rethinking the Power of Data-Driven Optimization Routinecited by 0
  30. 2024Rician Denoising Diffusion Probabilistic Models For Sodium Breast MRI Enhancementcited by 0
  31. 2025SNRAware: Improved Deep Learning MRI Denoising with SNR Unit Training and G-factor Map Augmentationcited by 0
  32. 2025Efficient Noise Calculation in Deep Learning-based MRI Reconstructionscited by 0
  33. 2025Enhancing Diffusion-Weighted Images (DWI) for Diffusion MRI: Is it Enough without Non-Diffusion-Weighted B=0 Reference?cited by 0
  34. 2025What is Adversarial Training for Diffusion Models?cited by 0
  35. 2025MID: A Self-supervised Multimodal Iterative Denoising Frameworkcited by 0
  36. 2026SSPFormer: Self-Supervised Pretrained Transformer for MRI Imagescited by 0
  37. 2026TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIscited by 0
  38. 2026Joint Medical Image Enhancement and Segmentation with Diffusion-based Symbiotic Information Interactioncited by 0

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  1. 2025Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data
  2. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review
  3. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Survey
  4. 2024Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation
  5. 2024Self-Consistent Recursive Diffusion Bridge for Medical Image Translation
  6. 2026VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation
  7. 2022Supervised Denoising of Diffusion-Weighted Magnetic Resonance Images Using a Convolutional Neural Network and Transfer Learning
  8. 2023Denoising Diffusion Bridge Models