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Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network

arXiv 2003.13815 ↗First posted 26 Mar 2020eess.IV cs.CV cs.LGcited by 43

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Abstract (arXiv)

Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNNs) for image recognition and classification. However, due to the limited availability of annotated medical images, the classification of medical images remains the biggest challenge in medical diagnosis. Thanks to transfer learning, an effective mechanism that can provide a promising solution by transferring knowledge from generic object recognition tasks to domain-specific tasks. In this paper, we validate and adapt our previously developed CNN, called Decompose, Transfer, and Compose (DeTraC), for the classification of COVID-19 chest X-ray images. DeTraC can deal with any irregularities in the image dataset by investigating its class boundaries using a class decomposition mechanism. The experimental results showed the capability of DeTraC in the detection of COVID-19 cases from a comprehensive image dataset collected from several hospitals around the world. High accuracy of 95.12% (with a sensitivity of 97.91%, a specificity of 91.87%, and a precision of 93.36%) was achieved by DeTraC in the detection of COVID-19 X-ray images from normal, and severe acute respiratory syndrome cases.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 20; 2022: 7; 2023: 7; 2024: 5; 2025: 3; 2026: 1.

43 papers.

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  1. 2021COVID-Net CXR-2: An Enhanced Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-ray Imagescited by 22
  2. 2021Self-supervised deep convolutional neural network for chest X-ray classificationcited by 16
  3. 2021I Find Your Lack of Uncertainty in Computer Vision Disturbingcited by 16
  4. 2022BCS-Net: Boundary, Context and Semantic for Automatic COVID-19 Lung Infection Segmentation from CT Imagescited by 16
  5. 2022A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicroncited by 13
  6. 2021Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray imagescited by 10
  7. 2021UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detectioncited by 8
  8. 2022Spatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scanscited by 7
  9. 2021A novel framework based on deep learning and ANOVA feature selection method for diagnosis of COVID-19 cases from chest X-ray Imagescited by 6
  10. 2022BIO-CXRNET: A Robust Multimodal Stacking Machine Learning Technique for Mortality Risk Prediction of COVID-19 Patients using Chest X-Ray Images and Clinical Datacited by 4
  11. 2021Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Reviewcited by 3
  12. 2021Classification of COVID-19 on chest X-Ray images using Deep Learning model with Histogram Equalization and Lungs Segmentationcited by 3
31 more
  1. 2022Classification of COVID-19 in Chest X-ray Images Using Fusion of Deep Features and LightGBMcited by 3
  2. 2023Deep Reinforcement Learning Framework for Thoracic Diseases Classification via Prior Knowledge Guidancecited by 3
  3. 2021COVID-19 identification from volumetric chest CT scans using a progressively resized 3D-CNN incorporating segmentation, augmentation, and class-rebalancingcited by 2
  4. 2025CLOG-CD: Curriculum Learning based on Oscillating Granularity of Class Decomposed Medical Image Classificationcited by 2
  5. 2021Real-time Prediction for Mechanical Ventilation in COVID-19 Patients using A Multi-task Gaussian Process Multi-objective Self-attention Networkcited by 1
  6. 2021Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounderscited by 1
  7. 2021A Survey of Machine Learning Techniques for Detecting and Diagnosing COVID-19 from Imagingcited by 1
  8. 2021CrossedWires: A Dataset of Syntactically Equivalent but Semantically Disparate Deep Learning Modelscited by 1
  9. 2021Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the Systemcited by 1
  10. 2021CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Imagescited by 1
  11. 2023Fitness Dependent Optimizer with Neural Networks for COVID-19 patientscited by 1
  12. 2023Transfer learning method in the problem of binary classification of chest X-rayscited by 1
  13. 2023Making the Invisible Visible: Toward High-Quality Terahertz Tomographic Imaging via Physics-Guided Restorationcited by 1
  14. 2023COVID-19 Diagnosis: ULGFBP-ResNet51 approach on the CT and the Chest X-ray Images Classificationcited by 1
  15. 2024Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learningcited by 1
  16. 2024Enhancing Brain Tumor Classification Using TrAdaBoost and Multi-Classifier Deep Learning Approachescited by 1
  17. 2021Ebola Optimization Search Algorithm (EOSA): A new metaheuristic algorithm based on the propagation model of Ebola virus diseasecited by 0
  18. 2021A Data Augmented Approach to Transfer Learning for Covid-19 Detectioncited by 0
  19. 2021Recognition of COVID-19 Disease Utilizing X-Ray Imaging of the Chest Using CNNcited by 0
  20. 2021Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rayscited by 0
  21. 2021Neural Networks for Infectious Diseases Detection: Prospects and Challengescited by 0
  22. 2022Comparative Analysis of State-of-the-Art Deep Learning Models for Detecting COVID-19 Lung Infection from Chest X-Ray Imagescited by 0
  23. 2022Diagnosis of COVID-19 disease using CT scan images and pre-trained modelscited by 0
  24. 2023CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classificationcited by 0
  25. 2023Deep Residual CNN for Multi-Class Chest Infection Diagnosiscited by 0
  26. 2024Empowering Medical Imaging with Artificial Intelligence: A Review of Machine Learning Approaches for the Detection, and Segmentation of COVID-19 Using Radiographic and Tomographic Imagescited by 0
  27. 2024Automatic Detection of COVID-19 from Chest X-ray Images Using Deep Learning Modelcited by 0
  28. 2024From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19cited by 0
  29. 2025Application of discrete Ricci curvature in pruning randomly wired neural networks: A case study with chest x-ray classification of COVID-19cited by 0
  30. 2025No Labels Needed: Zero-Shot Image Classification with Collaborative Self-Learningcited by 0
  31. 2026On-Device Continual Learning with Dual-Stage Buffer and Dynamic Loss for Point-of-Care Pneumonia Diagnosiscited by 0