mlsanityData to 7 Oct 2026

Diffusion Probabilistic Models beat GANs on Medical Images

arXiv 2212.07501 ↗First posted 14 Dec 2022eess.IV cs.CVcited by 77

On the map: Diffusion models → Medical imaging and segmentation

Abstract (arXiv)

The success of Deep Learning applications critically depends on the quality and scale of the underlying training data. Generative adversarial networks (GANs) can generate arbitrary large datasets, but diversity and fidelity are limited, which has recently been addressed by denoising diffusion probabilistic models (DDPMs) whose superiority has been demonstrated on natural images. In this study, we propose Medfusion, a conditional latent DDPM for medical images. We compare our DDPM-based model against GAN-based models, which constitute the current state-of-the-art in the medical domain. Medfusion was trained and compared with (i) StyleGan-3 on n=101,442 images from the AIROGS challenge dataset to generate fundoscopies with and without glaucoma, (ii) ProGAN on n=191,027 from the CheXpert dataset to generate radiographs with and without cardiomegaly and (iii) wGAN on n=19,557 images from the CRCMS dataset to generate histopathological images with and without microsatellite stability. In the AIROGS, CRMCS, and CheXpert datasets, Medfusion achieved lower (=better) FID than the GANs (11.63 versus 20.43, 30.03 versus 49.26, and 17.28 versus 84.31). Also, fidelity (precision) and diversity (recall) were higher (=better) for Medfusion in all three datasets. Our study shows that DDPM are a superior alternative to GANs for image synthesis in the medical domain.

Key facts. Cited by 77 papers in the map (data through 7 Oct 2026). Placed in Medical imaging and segmentation, one of 14 directions in Diffusion models. Builds on 24 of its 48 references that are in the map. First posted on arXiv 14 Dec 2022.

Builds on

24 of 48 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems2 Nov
  2. 2022A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images27 Sep
  3. 2022Brain Imaging Generation with Latent Diffusion Models15 Sep

Other references · 21

  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. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  7. 2020Denoising Diffusion Implicit Modelscited by 9,655
  8. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  9. 2022Generative Adversarial Networkscited by 5,603
  10. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  11. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  12. 2016Improved Techniques for Training GANscited by 2,938
9 more
  1. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,410
  2. 2018Demystifying MMD GANscited by 1,268
  3. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  4. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  5. 2018Pros and Cons of GAN Evaluation Measurescited by 224
  6. 2018MedGAN: Medical Image Translation using GANscited by 152
  7. 2021Pros and Cons of GAN Evaluation Measures: New Developmentscited by 121
  8. 2015How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?cited by 45
  9. 2021GAN-based Data Augmentation for Chest X-ray Classificationcited by 18

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 16; 2025: 35; 2026: 19.

77 papers.

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  1. 2023PathLDM: Text conditioned Latent Diffusion Model for Histopathologycited by 51
  2. 2023Learned representation-guided diffusion models for large-image generationcited by 39
  3. 20243D MedDiffusion: A 3D Medical Latent Diffusion Model for Controllable and High-quality Medical Image Generationcited by 37
  4. 2023Generative quantum machine learning via denoising diffusion probabilistic modelscited by 30
  5. 2024Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolutioncited by 29
  6. 2024Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challengescited by 24
  7. 2024Similarity and Quality Metrics for MR Image-To-Image Translationcited by 20
  8. 2024ZoomLDM: Latent Diffusion Model for multi-scale image generationcited by 15
  9. 2025PixCell: A generative foundation model for digital histopathology imagescited by 11
  10. 2025A Pragmatic Note on Evaluating Generative Models with Fr'echet Inception Distance for Retinal Image Synthesiscited by 8
  11. 2025PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditionscited by 8
  12. 2024On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Modelscited by 7
38 more
  1. 2025Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Datacited by 7
  2. 2023CT Reconstruction using Diffusion Posterior Sampling conditioned on a Nonlinear Measurement Modelcited by 6
  3. 2024Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Surveycited by 6
  4. 2025Domain-randomized deep learning for neuroimage analysiscited by 6
  5. 2024Annotated Biomedical Video Generation using Denoising Diffusion Probabilistic Models and Flow Fieldscited by 5
  6. 2025Prompt to Polyp: Medical Text-Conditioned Image Synthesis with Diffusion Modelscited by 5
  7. 2025RetinaLogos: Fine-Grained Synthesis of High-Resolution Retinal Images Through Captionscited by 5
  8. 2025Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusioncited by 5
  9. 2026FlowLet: Conditional 3D Brain MRI Synthesis using Wavelet Flow Matchingcited by 5
  10. 2023Data Augmentation for Environmental Sound Classification Using Diffusion Probabilistic Model with Top-k Selection Discriminatorcited by 4
  11. 2023Gaussian Harmony: Attaining Fairness in Diffusion-based Face Generation Modelscited by 4
  12. 2024Report on the AAPM Grand Challenge on deep generative modeling for learning medical image statisticscited by 4
  13. 2025LAND: Lung and Nodule Diffusion for 3D Chest CT Synthesis with Anatomical Guidancecited by 4
  14. 2023Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathologycited by 3
  15. 2025SurGrID: Controllable Surgical Simulation via Scene Graph to Image Diffusioncited by 3
  16. 2025Diffusion models applied to skin and oral cancer classificationcited by 3
  17. 2025Diffusion-Based Data Augmentation for Medical Image Segmentationcited by 3
  18. 2025Radiology Report Conditional 3D CT Generation with Multi Encoder Latent diffusion Modelcited by 3
  19. 2024ContourDiff: Unpaired Medical Image Translation with Structural Consistencycited by 2
  20. 2024Uncovering Hidden Subspaces in Video Diffusion Models Using Re-Identificationcited by 2
  21. 2024Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K Samplingcited by 2
  22. 2025Diffusion Bridge Models for 3D Medical Image Translationcited by 2
  23. 2025VAP-Diffusion: Enriching Descriptions with MLLMs for Enhanced Medical Image Generationcited by 2
  24. 2025PanoDiff-SR: Synthesizing Dental Panoramic Radiographs using Diffusion and Super-resolutioncited by 2
  25. 2025Flow Matching for Conditional MRI-CT and CBCT-CT Image Synthesiscited by 2
  26. 2026FOSCU: Feasibility of Synthetic MRI Generation via Duo-Diffusion Models for Enhancement of 3D U-Nets in Hepatic Segmentationcited by 2
  27. 2024Unleashing the Potential of Synthetic Images: A Study on Histopathology Image Classificationcited by 1
  28. 2024Advancing Histopathology with Deep Learning Under Data Scarcity: A Decade in Reviewcited by 1
  29. 2025GAUDA: Generative Adaptive Uncertainty-guided Diffusion-based Augmentation for Surgical Segmentationcited by 1
  30. 2025CQ CNN: A Hybrid Classical Quantum Convolutional Neural Network for Alzheimer's Disease Detection Using Diffusion Generated and U Net Segmented 3D MRIcited by 1
  31. 2025AI Alignment in Medical Imaging: Unveiling Hidden Biases Through Counterfactual Analysiscited by 1
  32. 2025ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesiscited by 1
  33. 2025Breast Cancer Detection in Thermographic Images via Diffusion-Based Augmentation and Nonlinear Feature Fusioncited by 1
  34. 2025Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusioncited by 1
  35. 2026Generalizing Score-based generative models for Heavy-tailed Distributionscited by 1
  36. 2026Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025cited by 1
  37. 2026WaveDiT: Distribution-Aware Wavelet Flow Matching for Efficient 3D Brain MRI Synthesiscited by 1
  38. 2026MUMINS: Metadata-conditioned Uncertainty-aware Medical Image Next-state Synthesiscited by 1

50 most cited of 77 All 77 (JSON)

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  1. 2024Deep Generative Models for 3D Medical Image Synthesis
  2. 2024Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation
  3. 2022Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report
  4. 2024Cross-conditioned Diffusion Model for Medical Image to Image Translation
  5. 2023Assessing the capacity of a denoising diffusion probabilistic model to reproduce spatial context
  6. 2025fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
  7. 2024Multi-Conditioned Denoising Diffusion Probabilistic Model (mDDPM) for Medical Image Synthesis
  8. 2023Denoising Diffusion Probabilistic Models as a Defense against Adversarial Attacks