mlsanityData to 7 Oct 2026

Unsupervised Medical Image Translation with Adversarial Diffusion Models

arXiv 2207.08208 ↗First posted 17 Jul 2022eess.IV cs.CVcited by 191

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

Imputation of missing images via source-to-target modality translation can improve diversity in medical imaging protocols. A pervasive approach for synthesizing target images involves one-shot mapping through generative adversarial networks (GAN). Yet, GAN models that implicitly characterize the image distribution can suffer from limited sample fidelity. Here, we propose a novel method based on adversarial diffusion modeling, SynDiff, for improved performance in medical image translation. To capture a direct correlate of the image distribution, SynDiff leverages a conditional diffusion process that progressively maps noise and source images onto the target image. For fast and accurate image sampling during inference, large diffusion steps are taken with adversarial projections in the reverse diffusion direction. To enable training on unpaired datasets, a cycle-consistent architecture is devised with coupled diffusive and non-diffusive modules that bilaterally translate between two modalities. Extensive assessments are reported on the utility of SynDiff against competing GAN and diffusion models in multi-contrast MRI and MRI-CT translation. Our demonstrations indicate that SynDiff offers quantitatively and qualitatively superior performance against competing baselines.

Key facts. Cited by 191 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 44 of its 86 references that are in the map. First posted on arXiv 17 Jul 2022.

Builds on

44 of 86 references.

Closest ancestors · 6

Same direction, newest first

  1. 2022Adaptive Diffusion Priors for Accelerated MRI Reconstruction12 Jul
  2. 2022A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion7 Jul
  3. 2022Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models7 Jun
  4. 2022Diffusion Models for Medical Anomaly Detection8 Mar
  5. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Models15 Nov
  6. 2021Score-based diffusion models for accelerated MRI8 Oct

Other references · 38

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  7. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  8. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  9. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  10. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,420
  11. 2018Self-Attention Generative Adversarial Networkscited by 809
  12. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
26 more
  1. 2018Which Training Methods for GANs do actually Converge?cited by 672
  2. 2017Unsupervised Image-to-Image Translation Networkscited by 602
  3. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
  4. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contractioncited by 306
  5. 2021Robust Compressed Sensing MRI with Deep Generative Priorscited by 284
  6. 2021ResViT: Residual vision transformers for multi-modal medical image synthesiscited by 177
  7. 2017Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Losscited by 161
  8. 2018MedGAN: Medical Image Translation using GANscited by 152
  9. 2021UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Modelscited by 133
  10. 2018Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networkscited by 131
  11. 2019Missing MRI Pulse Sequence Synthesis using Multi-Modal Generative Adversarial Networkcited by 98
  12. 2017Deep MR to CT Synthesis using Unpaired Datacited by 86
  13. 2020Hi-Net: Hybrid-fusion Network for Multi-modal MR Image Synthesiscited by 86
  14. 2021Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformerscited by 76
  15. 2022MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusioncited by 66
  16. 2018Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data sizecited by 42
  17. 2019DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesiscited by 36
  18. 2019mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesiscited by 34
  19. 2017Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Codingcited by 33
  20. 2019CollaGAN : Collaborative GAN for Missing Image Data Imputationcited by 33
  21. 2022Federated Learning of Generative Image Priors for MRI Reconstructioncited by 33
  22. 2018Deep CT to MR Synthesis using Paired and Unpaired Datacited by 31
  23. 2018Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGANcited by 31
  24. 2021Unsupervised Domain Adaptation with Variational Approximation for Cardiac Segmentationcited by 28
  25. 2021TranSMS: Transformers for Super-Resolution Calibration in Magnetic Particle Imagingcited by 18
  26. 2020Semi-Supervised Learning of Mutually Accelerated MRI Synthesis without Fully-Sampled Ground Truthscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 8; 2023: 32; 2024: 71; 2025: 48; 2026: 32.

191 papers.

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  1. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  2. 2022Diffusion Models in Vision: A Surveycited by 1,008
  3. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 269
  4. 2024Diffusion Model-Based Image Editing: A Surveycited by 212
  5. 2023Conditional Diffusion Models for Semantic 3D Brain MRI Synthesiscited by 85
  6. 2024Towards Generalizable Tumor Synthesiscited by 65
  7. 2023CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesiscited by 64
  8. 2024A Comprehensive Survey of Foundation Models in Medicinecited by 56
  9. 2024Endora: Video Generation Models as Endoscopy Simulatorscited by 53
  10. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  11. 2023Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Imagescited by 45
  12. 2023Zero-shot Medical Image Translation via Frequency-Guided Diffusion Modelscited by 39
38 more
  1. 2023Unified Multi-Modal Image Synthesis for Missing Modality Imputationcited by 39
  2. 20243D MedDiffusion: A 3D Medical Latent Diffusion Model for Controllable and High-quality Medical Image Generationcited by 37
  3. 2024Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generationcited by 33
  4. 2024Generative AI for Synthetic Data Generation: Methods, Challenges and the Futurecited by 31
  5. 2024Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolutioncited by 29
  6. 2024Self-Consistent Recursive Diffusion Bridge for Medical Image Translationcited by 26
  7. 2024I2I-Mamba: Multi-modal medical image synthesis via selective state space modelingcited by 26
  8. 2022A Diffusion Model Predicts 3D Shapes from 2D Microscopy Imagescited by 24
  9. 2024Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challengescited by 24
  10. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  11. 2024EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Modelscited by 23
  12. 2022Few-shot Image Generation with Diffusion Modelscited by 21
  13. 2023Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstructioncited by 20
  14. 2023Diffusion Models for Contrast Harmonization of Magnetic Resonance Imagescited by 19
  15. 2023Investigating Data Memorization in 3D Latent Diffusion Models for Medical Image Synthesiscited by 19
  16. 2024Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learningcited by 17
  17. 2023Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Actioncited by 15
  18. 2023MRI Reconstruction with Side Information using Diffusion Modelscited by 15
  19. 2023DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Datacited by 15
  20. 2023Denoising diffusion-based MRI to CT image translation enables automated spinal segmentationcited by 15
  21. 2023DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRIcited by 14
  22. 2024FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor Synthesiscited by 14
  23. 2024Are CLIP features all you need for Universal Synthetic Image Origin Attribution?cited by 14
  24. 2023Learning Fourier-Constrained Diffusion Bridges for MRI Reconstructioncited by 13
  25. 2024Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Imagescited by 13
  26. 2024Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse Problemscited by 13
  27. 2024Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Modelscited by 13
  28. 2025Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Datacited by 13
  29. 2025Metrics that matter: Evaluating image quality metrics for medical image generationcited by 12
  30. 2022One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstructioncited by 11
  31. 2024CATD: Unified Representation Learning for EEG-to-fMRI Cross-Modal Generationcited by 11
  32. 2024Analyzing Tumors by Synthesiscited by 11
  33. 2024DenoMamba: A fused state-space model for low-dose CT denoisingcited by 11
  34. 2023Semantic Image Synthesis for Abdominal CTcited by 10
  35. 2024PASTA: Pathology-Aware MRI to PET Cross-Modal Translation with Diffusion Modelscited by 10
  36. 2023DiffuseIR:Diffusion Models For Isotropic Reconstruction of 3D Microscopic Imagescited by 9
  37. 2023A Survey of Emerging Applications of Diffusion Probabilistic Models in MRIcited by 9
  38. 2024A Survey on Domain Generalization for Medical Image Analysiscited by 9

50 most cited of 191 All 191 (JSON)

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  1. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  2. 2025Benchmarking GANs, Diffusion Models, and Flow Matching for T1w-to-T2w MRI Translation
  3. 2025Comparative Analysis of GAN and Diffusion for MRI-to-CT translation
  4. 2026Cross Modality Image Translation In Medical Imaging Using Generative Frameworks
  5. 2024Deep Generative Models for 3D Medical Image Synthesis
  6. 2022Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report
  7. 2022Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models
  8. 2023Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis