mlsanityData to 7 Oct 2026

Soft-Label Anonymous Gastric X-ray Image Distillation

arXiv 2104.02857 ↗First posted 7 Apr 2021eess.IV cs.CVcited by 51

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Abstract (arXiv)

This paper presents a soft-label anonymous gastric X-ray image distillation method based on a gradient descent approach. The sharing of medical data is demanded to construct high-accuracy computer-aided diagnosis (CAD) systems. However, the large size of the medical dataset and privacy protection are remaining problems in medical data sharing, which hindered the research of CAD systems. The idea of our distillation method is to extract the valid information of the medical dataset and generate a tiny distilled dataset that has a different data distribution. Different from model distillation, our method aims to find the optimal distilled images, distilled labels and the optimized learning rate. Experimental results show that the proposed method can not only effectively compress the medical dataset but also anonymize medical images to protect the patient's private information. The proposed approach can improve the efficiency and security of medical data sharing.

Key facts. Cited by 51 papers in the map (data through 7 Oct 2026). Builds on 9 of its 28 references that are in the map. First posted on arXiv 7 Apr 2021.

Builds on

9 of 28 references.

References · 9

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  4. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,182
  5. 2015Gradient-based Hyperparameter Optimization through Reversible Learningcited by 357
  6. 2018Dataset Distillationcited by 224
  7. 2019Soft-Label Dataset Distillation and Text Dataset Distillationcited by 106
  8. 2017Practical Coreset Constructions for Machine Learningcited by 75
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 14; 2023: 7; 2024: 9; 2025: 10; 2026: 11.

51 papers.

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  1. 2022Dataset Distillation by Matching Training Trajectoriescited by 437
  2. 2022Dataset Distillation using Neural Feature Regressioncited by 177
  3. 2022Minimizing the Accumulated Trajectory Error to Improve Dataset Distillationcited by 142
  4. 2023Dataset Distillation: A Comprehensive Reviewcited by 126
  5. 2023Improved Distribution Matching for Dataset Condensationcited by 124
  6. 2022Privacy for Free: How does Dataset Condensation Help Privacy?cited by 119
  7. 2023A Comprehensive Survey of Dataset Distillationcited by 114
  8. 2023Data Distillation: A Surveycited by 86
  9. 2022Accelerating Dataset Distillation via Model Augmentationcited by 62
  10. 2022Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environmentscited by 49
  11. 2023Sequential Subset Matching for Dataset Distillationcited by 40
  12. 2022Compressed Gastric Image Generation Based on Soft-Label Dataset Distillation for Medical Data Sharingcited by 35
38 more
  1. 2022Dataset Distillation Using Parameter Pruningcited by 27
  2. 2022Dataset Distillation for Medical Dataset Sharingcited by 25
  3. 2024Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectorycited by 20
  4. 2024Importance-Aware Adaptive Dataset Distillationcited by 18
  5. 2024Generative Dataset Distillation: Balancing Global Structure and Local Detailscited by 18
  6. 2025Hyperbolic Dataset Distillationcited by 15
  7. 2024Generative Dataset Distillation Based on Diffusion Modelcited by 13
  8. 2025Diversity-Driven Generative Dataset Distillation Based on Diffusion Model with Self-Adaptive Memorycited by 10
  9. 2025Information-Guided Diffusion Sampling for Dataset Distillationcited by 10
  10. 2022Towards Robust Dataset Learningcited by 9
  11. 2025Task-Specific Generative Dataset Distillation with Difficulty-Guided Samplingcited by 8
  12. 2022COVID-19 Detection Based on Self-Supervised Transfer Learning Using Chest X-Ray Imagescited by 7
  13. 2025MGD3: Mode-Guided Dataset Distillation using Diffusion Modelscited by 6
  14. 2025Decoupled Audio-Visual Dataset Distillationcited by 6
  15. 2024Progressive trajectory matching for medical dataset distillationcited by 5
  16. 2024Label-Augmented Dataset Distillationcited by 5
  17. 2025Generative Dataset Distillation Based on Self-knowledge Distillationcited by 5
  18. 2024Dataset Distillation in Medical Imaging: A Feasibility Studycited by 4
  19. 2024Dataset Distillation for Histopathology Image Classificationcited by 4
  20. 2022Boosting Automatic COVID-19 Detection Performance with Self-Supervised Learning and Batch Knowledge Ensemblingcited by 3
  21. 2025High-Order Progressive Trajectory Matching for Medical Image Dataset Distillationcited by 2
  22. 2026ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillationcited by 2
  23. 2026FD2: A Dedicated Framework for Fine-Grained Dataset Distillationcited by 2
  24. 2022Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Contextcited by 1
  25. 2022RGMIM: Region-Guided Masked Image Modeling for Learning Meaningful Representations from X-Ray Imagescited by 1
  26. 2023Detecting the open-world objects with the help of the Braincited by 1
  27. 2026Closed-Form Linear-Probe Dataset Distillation for Pre-trained Vision Modelscited by 1
  28. 2023Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matchingcited by 0
  29. 2024UDD: Dataset Distillation via Mining Underutilized Regionscited by 0
  30. 2025ACE: A Cardinality Estimator for Set-Valued Queriescited by 0
  31. 2025Dataset Distillation with Probabilistic Latent Featurescited by 0
  32. 2026Foreground-Aware Dataset Distillation via Dynamic Patch Selectioncited by 0
  33. 2026Difficulty-guided Sampling: Bridging the Target Gap between Dataset Distillation and Downstream Taskscited by 0
  34. 2026Multimodal Dataset Distillation Made Simple by Prototype-Guided Data Synthesiscited by 0
  35. 2026JDCNet: Confidence-Gated Privileged-Modality Distillation for Cost-Preserving X-ray Inferencecited by 0
  36. 2026SAS: Semantic-aware Sampling for Generative Dataset Distillationcited by 0
  37. 2026Efficient Video Dataset Distillation via Cluster-Guided Prototype Blendingcited by 0
  38. 2026DeCO: Discriminative Evidence Composition for Fine-Grained Dataset Distillationcited by 0

50 most cited of 51 All 51 (JSON)