mlsanityData to 7 Oct 2026

Deep Learning for Chest X-ray Analysis: A Survey

arXiv 2103.08700 ↗First posted 15 Mar 2021eess.IV cs.CVcited by 84

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Abstract (arXiv)

Recent advances in deep learning have led to a promising performance in many medical image analysis tasks. As the most commonly performed radiological exam, chest radiographs are a particularly important modality for which a variety of applications have been researched. The release of multiple, large, publicly available chest X-ray datasets in recent years has encouraged research interest and boosted the number of publications. In this paper, we review all studies using deep learning on chest radiographs, categorizing works by task: image-level prediction (classification and regression), segmentation, localization, image generation and domain adaptation. Commercially available applications are detailed, and a comprehensive discussion of the current state of the art and potential future directions are provided.

Key facts. Cited by 84 papers in the map (data through 7 Oct 2026). Builds on 120 of its 407 references that are in the map. First posted on arXiv 15 Mar 2021.

Builds on

120 of 407 references.

References · 120

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50 most cited of 120 All 120 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 23; 2023: 17; 2024: 19; 2025: 14; 2026: 7.

84 papers.

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  1. 2022MedCLIP: Contrastive Learning from Unpaired Medical Images and Textcited by 564
  2. 2024Exploring scalable medical image encoders beyond text supervisioncited by 129
  3. 2024AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detectioncited by 126
  4. 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Modelscited by 101
  5. 2022Delving into Masked Autoencoders for Multi-Label Thorax Disease Classificationcited by 65
  6. 2024Review of multimodal machine learning approaches in healthcarecited by 30
  7. 2022Risk of Bias in Chest Radiography Deep Learning Foundation Modelscited by 26
  8. 2025RadVLM: A Multitask Conversational Vision-Language Model for Radiologycited by 24
  9. 2023Beware of diffusion models for synthesizing medical images -- A comparison with GANs in terms of memorizing brain MRI and chest x-ray imagescited by 23
  10. 2023A Recent Survey of Vision Transformers for Medical Image Segmentationcited by 22
  11. 2024EVA-X: A Foundation Model for General Chest X-ray Analysis with Self-supervised Learningcited by 22
  12. 2022Deep Learning for Computational Cytology: A Surveycited by 20
38 more
  1. 2022Membership Inference Attack Using Self Influence Functionscited by 19
  2. 2024MedVH: Towards Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Contextcited by 19
  3. 2022Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rayscited by 17
  4. 2023Learning A Multi-Task Transformer Via Unified And Customized Instruction Tuning For Chest Radiograph Interpretationcited by 14
  5. 2022A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicroncited by 13
  6. 2022Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Datacited by 8
  7. 2023Explainable Knowledge Distillation for On-device Chest X-Ray Classificationcited by 7
  8. 2024Nodule detection and generation on chest X-rays: NODE21 Challengecited by 7
  9. 2024FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentationcited by 7
  10. 2025Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Datacited by 7
  11. 2022Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Surveycited by 6
  12. 2025Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representationscited by 6
  13. 2022Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamesecited by 5
  14. 2022Did You Get What You Paid For? Rethinking Annotation Cost of Deep Learning Based Computer Aided Detection in Chest Radiographscited by 5
  15. 2026A unified multi-task framework enables interpretable chest radiograph analysiscited by 5
  16. 2022Gaze-Guided Class Activation Mapping: Leveraging Human Attention for Network Attention in Chest X-rays Classificationcited by 4
  17. 2022Multi-task UNet: Jointly Boosting Saliency Prediction and Disease Classification on Chest X-ray Imagescited by 4
  18. 2022Improving Classification Model Performance on Chest X-Rays through Lung Segmentationcited by 4
  19. 2024Learning Low-Rank Feature for Thorax Disease Classificationcited by 4
  20. 2024LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation Modelscited by 4
  21. 2025X-Ray-CoT: Interpretable Chest X-ray Diagnosis with Vision-Language Models via Chain-of-Thought Reasoningcited by 4
  22. 2022Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generatorscited by 3
  23. 2023Leveraging Anatomical Constraints with Uncertainty for Pneumothorax Segmentationcited by 3
  24. 2021CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge Distillationcited by 2
  25. 2023Employing similarity to highlight differences: On the impact of anatomical assumptions in chest X-ray registration methodscited by 2
  26. 2023Integrating Eye-Gaze Data into CXR DL Approaches: A Preliminary studycited by 2
  27. 2023Is visual explanation with Grad-CAM more reliable for deeper neural networks? a case study with automatic pneumothorax diagnosiscited by 2
  28. 2024[Citation needed] Data usage and citation practices in medical imaging conferencescited by 2
  29. 2024Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Imagescited by 2
  30. 2024Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learningcited by 2
  31. 2025Limitations of Public Chest Radiography Datasets for Artificial Intelligence: Label Quality, Domain Shift, Bias and Evaluation Challengescited by 2
  32. 2025AnyCXR: Human Anatomy Segmentation of Chest X-ray at Any Acquisition Position using Multi-stage Domain Randomized Synthetic Data with Imperfect Annotations and Conditional Joint Annotation Regularization Learningcited by 2
  33. 2026Mask-Guided Attention Regulation for Anatomically Consistent Counterfactual CXR Synthesiscited by 2
  34. 2021Impact of class imbalance on chest x-ray classifiers: towards better evaluation practices for discrimination and calibration performancecited by 1
  35. 2022Equine radiograph classification using deep convolutional neural networkscited by 1
  36. 2023Self-Supervised Curricular Deep Learning for Chest X-Ray Image Classificationcited by 1
  37. 2023StudyFormer : Attention-Based and Dynamic Multi View Classifier for X-ray imagescited by 1
  38. 2025Assessing the Distributional Fidelity of Synthetic Chest X-rays using the Embedded Characteristic Scorecited by 1

50 most cited of 84 All 84 (JSON)