mlsanityData to 14 Oct 2026

Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction

arXiv 2203.03623 ↗First posted 5 Mar 2022eess.IV cs.CVcited by 65

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

We propose a novel and unified method, measurement-conditioned denoising diffusion probabilistic model (MC-DDPM), for under-sampled medical image reconstruction based on DDPM. Different from previous works, MC-DDPM is defined in measurement domain (e.g. k-space in MRI reconstruction) and conditioned on under-sampling mask. We apply this method to accelerate MRI reconstruction and the experimental results show excellent performance, outperforming full supervision baseline and the state-of-the-art score-based reconstruction method. Due to its generative nature, MC-DDPM can also quantify the uncertainty of reconstruction. Our code is available on github.

Key facts. Cited by 65 papers in the map (data through 14 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 21 of its 25 references that are in the map. First posted on arXiv 5 Mar 2022.

Builds on

21 of 25 references.

Closest ancestors · 2

Same direction, newest first

  1. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Models15 Nov
  2. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 19

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  7. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
  8. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  9. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  10. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,354
  11. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 635
  12. 2018fastMRI: An Open Dataset and Benchmarks for Accelerated MRIcited by 470
7 more
  1. 2017MoDL: Model Based Deep Learning Architecture for Inverse Problemscited by 387
  2. 2017Learning a Variational Network for Reconstruction of Accelerated MRI Datacited by 342
  3. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 286
  4. 2020Permutation Invariant Graph Generation via Score-Based Generative Modelingcited by 270
  5. 2017Framing U-Net via Deep Convolutional Framelets: Application to Sparse-view CTcited by 88
  6. 2018JSR-Net: A Deep Network for Joint Spatial-Radon Domain CT Reconstruction from incomplete datacited by 6
  7. 2022Trained Model in Supervised Deep Learning is a Conditional Risk Minimizercited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 8; 2023: 18; 2024: 18; 2025: 13; 2026: 8.

65 papers.

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  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,114
  2. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 273
  3. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagerycited by 131
  4. 2022GENIE: Higher-Order Denoising Diffusion Solverscited by 127
  5. 2022Adaptive Diffusion Priors for Accelerated MRI Reconstructioncited by 118
  6. 2024MAISI: Medical AI for Synthetic Imagingcited by 87
  7. 2022DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstructioncited by 74
  8. 2024Towards Generalizable Tumor Synthesiscited by 65
  9. 2023How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Controlcited by 50
  10. 2023GSURE-Based Diffusion Model Training with Corrupted Datacited by 40
  11. 2023Self-Supervised MRI Reconstruction with Unrolled Diffusion Modelscited by 38
  12. 2024Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolutioncited by 30
38 more
  1. 2024Hallucination Index: An Image Quality Metric for Generative Reconstruction Modelscited by 26
  2. 2023Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstructioncited by 22
  3. 2023SMRD: SURE-based Robust MRI Reconstruction with Diffusion Modelscited by 16
  4. 2023Learning Fourier-Constrained Diffusion Bridges for MRI Reconstructioncited by 14
  5. 2023Correlated and Multi-frequency Diffusion Modeling for Highly Under-sampled MRI Reconstructioncited by 14
  6. 2024Timestep-Aware Correction for Quantized Diffusion Modelscited by 13
  7. 2025Text2CT: Towards 3D CT Volume Generation from Free-text Descriptions Using Diffusion Modelcited by 13
  8. 2025Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Datacited by 13
  9. 2022One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstructioncited by 12
  10. 2023SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRIcited by 12
  11. 2024Convergence Rate Analysis of LIONcited by 11
  12. 2023Uncertainty Estimation and Propagation in Accelerated MRI Reconstructioncited by 10
  13. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  14. 2022WKGM: Weight-K-space Generative Model for Parallel Imaging Reconstructioncited by 8
  15. 2023A Conditional Denoising Diffusion Probabilistic Model for Radio Interferometric Image Reconstructioncited by 6
  16. 2024Segmentation-guided MRI reconstruction for meaningfully diverse reconstructionscited by 6
  17. 2024Highly Accelerated MRI via Implicit Neural Representation Guided Posterior Sampling of Diffusion Modelscited by 5
  18. 2023Robust Physics-based Deep MRI Reconstruction Via Diffusion Purificationcited by 4
  19. 2023Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensemblescited by 4
  20. 2023Robust semi-supervised segmentation with timestep ensembling diffusion modelscited by 4
  21. 2023Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noisecited by 4
  22. 2024DP-MDM: Detail-Preserving MR Reconstruction via Multiple Diffusion Modelscited by 4
  23. 2024RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Modelscited by 4
  24. 2024FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbationcited by 4
  25. 2025Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Modelscited by 4
  26. 2024Volumetric Conditioning Module to Control Pretrained Diffusion Models for 3D Medical Imagescited by 3
  27. 2025Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problemscited by 3
  28. 2025Reconstruct or Generate: Exploring the Spectrum of Generative Modeling for Cardiac MRIcited by 3
  29. 2024Evaluating the Posterior Sampling Ability of Plug&Play Diffusion Methods in Sparse-View CTcited by 2
  30. 2024Sub-DM:Subspace Diffusion Model with Orthogonal Decomposition for MRI Reconstructioncited by 2
  31. 2025Mind the Detail: Uncovering Clinically Relevant Image Details in Accelerated MRI with Semantically Diverse Reconstructionscited by 2
  32. 2022Low-rank Tensor Assisted K-space Generative Model for Parallel Imaging Reconstructioncited by 1
  33. 2024ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstructioncited by 1
  34. 2024Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstructioncited by 1
  35. 2025Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Reviewcited by 1
  36. 2025MDPG: Multi-domain Diffusion Prior Guidance for MRI Reconstructioncited by 1
  37. 2025USB: Unified Synthetic Brain Framework for Bidirectional Pathology-Healthy Generation and Editingcited by 1
  38. 2026Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imagingcited by 1

50 most cited of 65 All 65 (JSON)

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  1. 2024Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation
  2. 2022Bayesian MRI Reconstruction with Joint Uncertainty Estimation using Diffusion Models
  3. 2023DDM2: Self-Supervised Diffusion MRI Denoising with Generative Diffusion Models
  4. 2025Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models
  5. 2023DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding
  6. 2022Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction
  7. 2022Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation
  8. 2024On Instabilities of Unsupervised Denoising Diffusion Models in Magnetic Resonance Imaging Reconstruction