mlsanityData to 7 Oct 2026

PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

arXiv 2203.10612 ↗First posted 20 Mar 2022eess.IV cs.CVcited by 19

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Abstract (arXiv)

The development of diagnostic models for detecting and diagnosing pediatric diseases in CXR scans is undertaken due to the lack of high-quality physician-annotated datasets. To overcome this challenge, we introduce and release PediCXR, a new pediatric CXR dataset of 9,125 studies retrospectively collected from a major pediatric hospital in Vietnam between 2020 and 2021. Each scan was manually annotated by a pediatric radiologist with more than ten years of experience. The dataset was labeled for the presence of 36 critical findings and 15 diseases. In particular, each abnormal finding was identified via a rectangle bounding box on the image. To the best of our knowledge, this is the first and largest pediatric CXR dataset containing lesion-level annotations and image-level labels for the detection of multiple findings and diseases. For algorithm development, the dataset was divided into a training set of 7,728 and a test set of 1,397. To encourage new advances in pediatric CXR interpretation using data-driven approaches, we provide a detailed description of the PediCXR data sample and make the dataset publicly available on https://physionet.org/content/pedicxr/1.0.0/

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). Builds on 10 of its 28 references that are in the map. First posted on arXiv 20 Mar 2022.

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10 of 28 references.

References · 10

  1. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,410
  2. 2017ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseasescited by 969
  3. 2017CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learningcited by 459
  4. 2019PadChest: A large chest x-ray image dataset with multi-label annotated reportscited by 308
  5. 2020VinDr-CXR: An open dataset of chest X-rays with radiologist's annotationscited by 236
  6. 2020Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease Dependencies and Uncertainty Labelscited by 56
  7. 2020COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray imagescited by 32
  8. 2020CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Settingcited by 18
  9. 2021DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scanscited by 11
  10. 2021Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networkscited by 7

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Citing papers per year: 2022: 2; 2023: 3; 2024: 4; 2025: 3; 2026: 7.

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  1. 2023Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Datacited by 176
  2. 2023Large-scale Long-tailed Disease Diagnosis on Radiology Imagescited by 17
  3. 2022An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiographcited by 7
  4. 2023K-Diag: Knowledge-enhanced Disease Diagnosis in Radiographic Imagingcited by 6
  5. 2025Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representationscited by 6
  6. 2022Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamesecited by 5
  7. 2024An Explainable Contrastive-based Dilated Convolutional Network with Transformer for Pediatric Pneumonia Detectioncited by 5
  8. 2025Diffusion-Based User-Guided Data Augmentation for Coronary Stenosis Detectioncited by 3
  9. 2024DiNO-Diffusion. Scaling Medical Diffusion via Self-Supervised Pre-Trainingcited by 2
  10. 2025Resolution scaling governs DINOv3 transfer performance in chest radiograph classificationcited by 2
  11. 2026A data- and compute-efficient chest X-ray foundation model beyond aggressive scalingcited by 2
  12. 2026MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imagingcited by 2
7 more
  1. 2024Improving Pediatric Pneumonia Diagnosis with Adult Chest X-ray Images Utilizing Contrastive Learning and Embedding Similaritycited by 0
  2. 2024Self-Supervised Learning for Building Robust Pediatric Chest X-ray Classification Modelscited by 0
  3. 2026ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Modelscited by 0
  4. 2026On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosiscited by 0
  5. 2026CANDOR: Chance-Calibrated Neighborhood Discordance in Frozen Encoders for Medical Imagingcited by 0
  6. 2026FRAME: Separating sampling variation from performance disparities in medical image analysiscited by 0
  7. 2026Cross-dataset transportability of pediatric chest X-ray deep learning across three countries: discrimination, calibration, operating-point failure, and limited-label recoverycited by 0