mlsanityData to 7 Oct 2026

Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks

arXiv 1807.10225 ↗First posted 26 Jul 2018cs.CV cs.LG stat.MLcited by 146

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Cited by 23 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Data diversity is critical to success when training deep learning models. Medical imaging data sets are often imbalanced as pathologic findings are generally rare, which introduces significant challenges when training deep learning models. In this work, we propose a method to generate synthetic abnormal MRI images with brain tumors by training a generative adversarial network using two publicly available data sets of brain MRI. We demonstrate two unique benefits that the synthetic images provide. First, we illustrate improved performance on tumor segmentation by leveraging the synthetic images as a form of data augmentation. Second, we demonstrate the value of generative models as an anonymization tool, achieving comparable tumor segmentation results when trained on the synthetic data versus when trained on real subject data. Together, these results offer a potential solution to two of the largest challenges facing machine learning in medical imaging, namely the small incidence of pathological findings, and the restrictions around sharing of patient data.

Key facts. Cited by 146 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jul 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 33; 2022: 30; 2023: 28; 2024: 19; 2025: 17; 2026: 19.

146 papers.

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  1. 2024MAISI: Medical AI for Synthetic Imagingcited by 86
  2. 2023Conditional Diffusion Models for Semantic 3D Brain MRI Synthesiscited by 85
  3. 2022EnvEdit: Environment Editing for Vision-and-Language Navigationcited by 83
  4. 2022Synthesizing Informative Training Samples with GANcited by 77
  5. 2021GANs for Medical Image Synthesis: An Empirical Studycited by 64
  6. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  7. 2021Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentationcited by 43
  8. 2023MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Imagescited by 41
  9. 2021VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformerscited by 28
  10. 2022Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Modelcited by 28
  11. 2021Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencodercited by 27
  12. 2021GAN-Based Data Augmentation and Anonymization for Skin-Lesion Analysis: A Critical Reviewcited by 25
38 more
  1. 2021Probing transfer learning with a model of synthetic correlated datasetscited by 24
  2. 2023DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Modelcited by 23
  3. 2023Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion modelscited by 19
  4. 2023Boosting Dermatoscopic Lesion Segmentation via Diffusion Models with Visual and Textual Promptscited by 17
  5. 2022Rethinking Surgical Instrument Segmentation: A Background Image Can Be All You Needcited by 16
  6. 2021Data synthesis and adversarial networks: A review and meta-analysis in cancer imagingcited by 15
  7. 2021Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Reviewcited by 15
  8. 2024Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNNcited by 15
  9. 2022FakeNews: GAN-based generation of realistic 3D volumetric data -- A systematic review and taxonomycited by 13
  10. 2025Text2CT: Towards 3D CT Volume Generation from Free-text Descriptions Using Diffusion Modelcited by 13
  11. 2023Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIscited by 12
  12. 2023Adversarial Fine-tuning using Generated Respiratory Sound to Address Class Imbalancecited by 11
  13. 2021Jekyll: Attacking Medical Image Diagnostics using Deep Generative Modelscited by 10
  14. 2023Semantic Image Synthesis for Abdominal CTcited by 10
  15. 2021Controllable cardiac synthesis via disentangled anatomy arithmeticcited by 9
  16. 2021TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentationcited by 9
  17. 2024Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Imagescited by 9
  18. 2021GAN Cocktail: mixing GANs without dataset accesscited by 8
  19. 2021CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysiscited by 8
  20. 2022Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Surveycited by 8
  21. 2022Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentificationcited by 8
  22. 2023Synthetic Data in Healthcarecited by 8
  23. 2024MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRIcited by 8
  24. 2022Sharing Generative Models Instead of Private Data: A Simulation Study on Mammography Patch Classificationcited by 7
  25. 2022Pathology Synthesis of 3D-Consistent Cardiac MR Images using 2D VAEs and GANscited by 7
  26. 2024Synthetic Data in Radiological Imaging: Current State and Future Outlookcited by 7
  27. 2021Ensembles of GANs for synthetic training data generationcited by 6
  28. 2021ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic Segmentationcited by 6
  29. 2022Adversarial Counterfactual Augmentation: Application in Alzheimer's Disease Classificationcited by 6
  30. 2023Denoising Diffusion Medical Modelscited by 6
  31. 2023Improving Small Language Models on PubMedQA via Generative Data Augmentationcited by 6
  32. 2023Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networkscited by 6
  33. 2021Improving prostate whole gland segmentation in t2-weighted MRI with synthetically generated datacited by 5
  34. 2021Learning of Inter-Label Geometric Relationships Using Self-Supervised Learning: Application To Gleason Grade Segmentationcited by 5
  35. 2022CS2: A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Interventioncited by 5
  36. 2022Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directionscited by 5
  37. 2022Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site datacited by 5
  38. 2023Towards Realistic Ultrasound Fetal Brain Imaging Synthesiscited by 5

50 most cited of 146 All 146 (JSON)