mlsanityData to 7 Oct 2026

GAN-Based Data Augmentation and Anonymization for Skin-Lesion Analysis: A Critical Review

arXiv 2104.10603 ↗First posted 20 Apr 2021eess.IV cs.CVcited by 25

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Abstract (arXiv)

Despite the growing availability of high-quality public datasets, the lack of training samples is still one of the main challenges of deep-learning for skin lesion analysis. Generative Adversarial Networks (GANs) appear as an enticing alternative to alleviate the issue, by synthesizing samples indistinguishable from real images, with a plethora of works employing them for medical applications. Nevertheless, carefully designed experiments for skin-lesion diagnosis with GAN-based data augmentation show favorable results only on out-of-distribution test sets. For GAN-based data anonymization - where the synthetic images replace the real ones - favorable results also only appear for out-of-distribution test sets. Because of the costs and risks associated with GAN usage, those results suggest caution in their adoption for medical applications.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 30 of its 49 references that are in the map. First posted on arXiv 20 Apr 2021.

Builds on

30 of 49 references.

References · 30

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18 more
  1. 2018Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networkscited by 146
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  10. 2019Skin Lesion Synthesis with Generative Adversarial Networkscited by 22
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  15. 2019Red blood cell image generation for data augmentation using Conditional Generative Adversarial Networkscited by 12
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Citing papers per year: 2022: 8; 2023: 6; 2024: 5; 2025: 5; 2026: 1.

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  1. 2023Generative models improve fairness of medical classifiers under distribution shiftscited by 90
  2. 2022A Survey on Deep Learning for Skin Lesion Segmentationcited by 22
  3. 2023AI-Generated Images as Data Source: The Dawn of Synthetic Eracited by 13
  4. 2022An Optimal Transport Perspective on Unpaired Image Super-Resolutioncited by 12
  5. 2022The (de)biasing effect of GAN-based augmentation methods on skin lesion imagescited by 9
  6. 2023Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptationcited by 9
  7. 2022Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasetscited by 6
  8. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  9. 2024GenFormer -- Generated Images are All You Need to Improve Robustness of Transformers on Small Datasetscited by 6
  10. 2022Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imagingcited by 4
  11. 2022Generative Adversarial Networks for Image Augmentation in Agriculture: A Systematic Reviewcited by 3
  12. 2025SafeTriage: Facial Video De-identification for Privacy-Preserving Stroke Triagecited by 3
13 more
  1. 2025eSkinHealth: A Multimodal Dataset for Neglected Tropical Skin Diseasescited by 3
  2. 2024Improving Deep Learning-based Automatic Cranial Defect Reconstruction by Heavy Data Augmentation: From Image Registration to Latent Diffusion Modelscited by 2
  3. 2024Variable-Speed Teaching-Playback as Real-World Data Augmentation for Imitation Learningcited by 2
  4. 2022A Robust Framework of Chromosome Straightening with ViT-Patch GANcited by 1
  5. 2023High Fidelity Synthetic Face Generation for Rosacea Skin Condition from Limited Datacited by 1
  6. 2023General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governancecited by 1
  7. 2024WasteGAN: Data Augmentation for Robotic Waste Sorting through Generative Adversarial Networkscited by 1
  8. 2024Local Lesion Generation is Effective for Capsule Endoscopy Image Data Augmentation in a Limited Data Settingcited by 1
  9. 2025Segmentation-Aware Generative Reinforcement Network (GRN) for Tissue Layer Segmentation in 3-D Ultrasound Images for Chronic Low-back Pain (cLBP) Assessmentcited by 1
  10. 2022GAN-based generative modelling for dermatological applications -- comparative studycited by 0
  11. 2025Optimizing Deep Learning for Skin Cancer Classification: A Computationally Efficient CNN with Minimal Accuracy Trade-Offcited by 0
  12. 2025AURAD: Anatomy-Pathology Unified Radiology Synthesis with Progressive Representationscited by 0
  13. 2026Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehiclescited by 0