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COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest CT Images

arXiv 2009.05383 ↗First posted 8 Sep 2020eess.IV cs.CV cs.LGcited by 39

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Abstract (arXiv)

The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease, there is a pressing need for rapid and effective screening tools to identify patients infected with COVID-19, and to this end CT imaging has been proposed as one of the key screening methods which may be used as a complement to RT-PCR testing, particularly in situations where patients undergo routine CT scans for non-COVID-19 related reasons, patients with worsening respiratory status or developing complications that require expedited care, and patients suspected to be COVID-19-positive but have negative RT-PCR test results. Motivated by this, in this study we introduce COVIDNet-CT, a deep convolutional neural network architecture that is tailored for detection of COVID-19 cases from chest CT images via a machine-driven design exploration approach. Additionally, we introduce COVIDx-CT, a benchmark CT image dataset derived from CT imaging data collected by the China National Center for Bioinformation comprising 104,009 images across 1,489 patient cases. Furthermore, in the interest of reliability and transparency, we leverage an explainability-driven performance validation strategy to investigate the decision-making behaviour of COVIDNet-CT, and in doing so ensure that COVIDNet-CT makes predictions based on relevant indicators in CT images. Both COVIDNet-CT and the COVIDx-CT dataset are available to the general public in an open-source and open access manner as part of the COVID-Net initiative. While COVIDNet-CT is not yet a production-ready screening solution, we hope that releasing the model and dataset will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon them.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Sep 2020.

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Citing papers per year: 2021: 18; 2022: 10; 2023: 3; 2024: 2; 2025: 6.

39 papers.

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  1. 2021COVID-Net CT-2: Enhanced Deep Neural Networks for Detection of COVID-19 from Chest CT Images Through Bigger, More Diverse Learningcited by 29
  2. 2021COVID-Net CXR-2: An Enhanced Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-ray Imagescited by 22
  3. 2021Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Datacited by 18
  4. 2021COVIDx-US -- An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analyticscited by 17
  5. 2021A methodology for training homomorphicencryption friendly neural networkscited by 10
  6. 2021TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases from Chest X-ray Imagescited by 8
  7. 2024Medical Unlearnable Examples: Securing Medical Data from Unauthorized Training via Sparsity-Aware Local Maskingcited by 8
  8. 2021Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learningcited by 7
  9. 2021COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Imagescited by 6
  10. 2021A 3D CNN Network with BERT For Automatic COVID-19 Diagnosis From CT-Scan Imagescited by 6
  11. 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
  12. 2025Generalizable and Explainable Deep Learning for Medical Image Computing: An Overviewcited by 6
27 more
  1. 2021Data Augmentation and CNN Classification For Automatic COVID-19 Diagnosis From CT-Scan Images On Small Datasetcited by 4
  2. 2023COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound Imagescited by 4
  3. 2023The Utility of the Virtual Imaging Trials Methodology for Objective Characterization of AI Systems and Training Datacited by 4
  4. 2021COVID-19 Detection from Chest X-ray Images using Imprinted Weights Approachcited by 3
  5. 2021COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imagingcited by 3
  6. 2022Virtual vs. Reality: External Validation of COVID-19 Classifiers using XCAT Phantoms for Chest Computed Tomographycited by 3
  7. 2022Classification of COVID-19 in Chest X-ray Images Using Fusion of Deep Features and LightGBMcited by 3
  8. 2022Transformer and GAN Based Super-Resolution Reconstruction Network for Medical Imagescited by 3
  9. 2021Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Imagescited by 2
  10. 2022Efficient Pruning for Machine Learning Under Homomorphic Encryptioncited by 2
  11. 2025Exploring Kernel Transformations for Implicit Neural Representationscited by 2
  12. 2021Systematic investigation into generalization of COVID-19 CT deep learning models with Gabor ensemble for lung involvement scoringcited by 1
  13. 2021Insights into Data through Model Behaviour: An Explainability-driven Strategy for Data Auditing for Responsible Computer Vision Applicationscited by 1
  14. 2022COVID-Net Biochem: An Explainability-driven Framework to Building Machine Learning Models for Predicting Survival and Kidney Injury of COVID-19 Patients from Clinical and Biochemistry Datacited by 1
  15. 2022COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT Imagescited by 1
  16. 2021Explainability Guided Multi-Site COVID-19 CT Classificationcited by 0
  17. 2021COVID-Net MLSys: Designing COVID-Net for the Clinical Workflowcited by 0
  18. 2022Improving COVID-19 CT Classification of CNNs by Learning Parameter-Efficient Representationcited by 0
  19. 2022COVID-Net Assistant: A Deep Learning-Driven Virtual Assistant for COVID-19 Symptom Prediction and Recommendationcited by 0
  20. 2022Explainable and Lightweight Model for COVID-19 Detection Using Chest Radiology Imagescited by 0
  21. 2022Evaluating Generalizability of Deep Learning Models Using Indian-COVID-19 CT Datasetcited by 0
  22. 2023NUMSnet: Nested-U Multi-class Segmentation network for 3D Medical Image Stackscited by 0
  23. 2024Density-based Isometric Mappingcited by 0
  24. 2025Classification based deep learning models for lung cancer and disease using medical imagescited by 0
  25. 2025GeMix: Conditional GAN-Based Mixup for Improved Medical Image Augmentationcited by 0
  26. 2025Domain Adaptation Techniques for Natural and Medical Image Classificationcited by 0
  27. 2025MORE: Multi-Organ Medical Image REconstruction Datasetcited by 0