mlsanityData to 7 Oct 2026

VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations

arXiv 2012.15029 ↗First posted 30 Dec 2020eess.IVcited by 236

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Cited by 37 in Multimodal LLMs / vision-language models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and localization of chest abnormalities. In this work, we describe a dataset of more than 100,000 chest X-ray scans that were retrospectively collected from two major hospitals in Vietnam. Out of this raw data, we release 18,000 images that were manually annotated by a total of 17 experienced radiologists with 22 local labels of rectangles surrounding abnormalities and 6 global labels of suspected diseases. The released dataset is divided into a training set of 15,000 and a test set of 3,000. Each scan in the training set was independently labeled by 3 radiologists, while each scan in the test set was labeled by the consensus of 5 radiologists. We designed and built a labeling platform for DICOM images to facilitate these annotation procedures. All images are made publicly available (https://www.physionet.org/content/vindr-cxr/1.0.0/) in DICOM format along with the labels of both the training set and the test set.

Key facts. Cited by 236 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Dec 2020.

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Citing papers per year: 2021: 11; 2022: 18; 2023: 39; 2024: 57; 2025: 58; 2026: 53.

236 papers.

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  1. 2022Making the Most of Text Semantics to Improve Biomedical Vision--Language Processingcited by 336
  2. 2024Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomographycited by 192
  3. 2023Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Datacited by 176
  4. 2024MAIRA-2: Grounded Radiology Report Generationcited by 140
  5. 2021TorchXRayVision: A library of chest X-ray datasets and modelscited by 131
  6. 2024Exploring scalable medical image encoders beyond text supervisioncited by 129
  7. 2024MMedAgent: Learning to Use Medical Tools with Multi-modal Agentcited by 108
  8. 2024CT2Rep: Automated Radiology Report Generation for 3D Medical Imagingcited by 96
  9. 2023CXR-CLIP: Toward Large Scale Chest X-ray Language-Image Pre-trainingcited by 81
  10. 2021Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reportscited by 80
  11. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  12. 2023LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matchingcited by 60
38 more
  1. 2021OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wildcited by 50
  2. 2023Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answeringcited by 41
  3. 2023CLIP in Medical Imaging: A Surveycited by 40
  4. 2025QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Trainingcited by 38
  5. 2024PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generationcited by 35
  6. 2021REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rayscited by 34
  7. 2021A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentationcited by 33
  8. 2021Federated Contrastive Learning for Decentralized Unlabeled Medical Imagescited by 33
  9. 2023CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray imagescited by 33
  10. 2023Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesiscited by 32
  11. 2022Explainable Deep Learning Methods in Medical Image Classification: A Surveycited by 31
  12. 2021VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labelscited by 27
  13. 2022Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Reviewcited by 27
  14. 2024MedIAnomaly: A comparative study of anomaly detection in medical imagescited by 25
  15. 2023Medical Vision Language Pretraining: A surveycited by 24
  16. 2024Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imagingcited by 24
  17. 2024Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Taskscited by 24
  18. 2025RadVLM: A Multitask Conversational Vision-Language Model for Radiologycited by 24
  19. 2021VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rayscited by 22
  20. 2023Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challengecited by 22
  21. 2024Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspectivecited by 22
  22. 2021Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexitycited by 21
  23. 2023PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentationcited by 21
  24. 2023UniChest: Conquer-and-Divide Pre-training for Multi-Source Chest X-Ray Classificationcited by 21
  25. 2022RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classificationcited by 19
  26. 2022PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in childrencited by 19
  27. 2024ChEX: Interactive Localization and Region Description in Chest X-rayscited by 18
  28. 2024Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learningcited by 18
  29. 2024Self-eXplainable AI for Medical Image Analysis: A Survey and New Outlookscited by 18
  30. 2025CheXWorld: Exploring Image World Modeling for Radiograph Representation Learningcited by 18
  31. 2023Large-scale Long-tailed Disease Diagnosis on Radiology Imagescited by 17
  32. 2024MedViLaM: A multimodal large language model with advanced generalizability and explainability for medical data understanding and generationcited by 17
  33. 2022Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clusteringcited by 16
  34. 2023Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learningcited by 16
  35. 2024You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learningcited by 16
  36. 2024M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretationcited by 16
  37. 2024Large Language Model Benchmarks in Medical Taskscited by 16
  38. 2022Significantly improving zero-shot X-ray pathology classification via fine-tuning pre-trained image-text encoderscited by 15

50 most cited of 236 All 236 (JSON)