mlsanityData to 7 Oct 2026

Dataset Distillation for Medical Dataset Sharing

arXiv 2209.14603 ↗First posted 29 Sep 2022cs.CR cs.CV cs.LGcited by 25

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Abstract (arXiv)

Sharing medical datasets between hospitals is challenging because of the privacy-protection problem and the massive cost of transmitting and storing many high-resolution medical images. However, dataset distillation can synthesize a small dataset such that models trained on it achieve comparable performance with the original large dataset, which shows potential for solving the existing medical sharing problems. Hence, this paper proposes a novel dataset distillation-based method for medical dataset sharing. Experimental results on a COVID-19 chest X-ray image dataset show that our method can achieve high detection performance even using scarce anonymized chest X-ray images.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 23 of its 33 references that are in the map. First posted on arXiv 29 Sep 2022.

Builds on

23 of 33 references.

References · 23

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  3. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  4. 2020Exploring Simple Siamese Representation Learningcited by 2,853
  5. 2020Dataset Condensation with Gradient Matchingcited by 510
  6. 2022Dataset Distillation by Matching Training Trajectoriescited by 437
  7. 2018Dynamic Few-Shot Visual Learning without Forgettingcited by 385
  8. 2021Dataset Condensation with Distribution Matchingcited by 362
  9. 2021Dataset Condensation with Differentiable Siamese Augmentationcited by 290
  10. 2020Dataset Meta-Learning from Kernel Ridge-Regressioncited by 230
  11. 2018Dataset Distillationcited by 224
  12. 2021Dataset Distillation with Infinitely Wide Convolutional Networkscited by 215
11 more
  1. 2022Dataset Distillation using Neural Feature Regressioncited by 177
  2. 2022Privacy for Free: How does Dataset Condensation Help Privacy?cited by 119
  3. 2019Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Datacited by 103
  4. 2020Flexible Dataset Distillation: Learn Labels Instead of Imagescited by 91
  5. 2017Practical Coreset Constructions for Machine Learningcited by 75
  6. 2020Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learningcited by 67
  7. 2021Soft-Label Anonymous Gastric X-ray Image Distillationcited by 51
  8. 2022Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environmentscited by 49
  9. 2022Sample Condensation in Online Continual Learningcited by 31
  10. 2021Condensed Composite Memory Continual Learningcited by 20
  11. 2022Self-Knowledge Distillation based Self-Supervised Learning for Covid-19 Detection from Chest X-Ray Imagescited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 5; 2024: 7; 2025: 7; 2026: 3.

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  1. 2023Dataset Distillation: A Comprehensive Reviewcited by 126
  2. 2023A Comprehensive Survey of Dataset Distillationcited by 114
  3. 2022Accelerating Dataset Distillation via Model Augmentationcited by 62
  4. 2023A Survey on Dataset Distillation: Approaches, Applications and Future Directionscited by 32
  5. 2024Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchorscited by 21
  6. 2024Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectorycited by 20
  7. 2024Importance-Aware Adaptive Dataset Distillationcited by 18
  8. 2024Generative Dataset Distillation: Balancing Global Structure and Local Detailscited by 18
  9. 2024Generative Dataset Distillation Based on Diffusion Modelcited by 13
  10. 2025Information-Guided Diffusion Sampling for Dataset Distillationcited by 10
  11. 2025Task-Specific Generative Dataset Distillation with Difficulty-Guided Samplingcited by 8
  12. 2023Federated Learning on Virtual Heterogeneous Data with Local-global Distillationcited by 6
13 more
  1. 2024Image Distillation for Safe Data Sharing in Histopathologycited by 6
  2. 2025Decoupled Audio-Visual Dataset Distillationcited by 6
  3. 2024Progressive trajectory matching for medical dataset distillationcited by 5
  4. 2025Generative Dataset Distillation Based on Self-knowledge Distillationcited by 5
  5. 2022Boosting Automatic COVID-19 Detection Performance with Self-Supervised Learning and Batch Knowledge Ensemblingcited by 3
  6. 2023Boosting the Cross-Architecture Generalization of Dataset Distillation through an Empirical Studycited by 3
  7. 2025High-Order Progressive Trajectory Matching for Medical Image Dataset Distillationcited by 2
  8. 2022RGMIM: Region-Guided Masked Image Modeling for Learning Meaningful Representations from X-Ray Imagescited by 1
  9. 2025Efficient and Privacy-Preserved Link Prediction via Condensed Graphscited by 0
  10. 2025Dataset Distillation with Probabilistic Latent Featurescited by 0
  11. 2026Foreground-Aware Dataset Distillation via Dynamic Patch Selectioncited by 0
  12. 2026Difficulty-guided Sampling: Bridging the Target Gap between Dataset Distillation and Downstream Taskscited by 0
  13. 2026Efficient Video Dataset Distillation via Cluster-Guided Prototype Blendingcited by 0