mlsanityData to 7 Oct 2026

Self-supervised deep convolutional neural network for chest X-ray classification

arXiv 2103.03055 ↗First posted 4 Mar 2021eess.IV cs.CV cs.NEcited by 16

Not on the map. Why?

Abstract (arXiv)

Chest radiography is a relatively cheap, widely available medical procedure that conveys key information for making diagnostic decisions. Chest X-rays are almost always used in the diagnosis of respiratory diseases such as pneumonia or the recent COVID-19. In this paper, we propose a self-supervised deep neural network that is pretrained on an unlabeled chest X-ray dataset. The learned representations are transferred to downstream task - the classification of respiratory diseases. The results obtained on four public datasets show that our approach yields competitive results without requiring large amounts of labeled training data.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 41 of its 64 references that are in the map. First posted on arXiv 4 Mar 2021.

Builds on

41 of 64 references.

References · 41

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  4. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  5. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  6. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
  7. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  8. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  9. 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,838
  10. 2018Unsupervised Representation Learning by Predicting Image Rotationscited by 1,586
  11. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  12. 2019CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparisoncited by 1,410
29 more
  1. 2016Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzlescited by 1,379
  2. 2019Self-Supervised Learning of Pretext-Invariant Representationscited by 806
  3. 2020Self-supervised Learning: Generative or Contrastivecited by 693
  4. 2019Data-Efficient Image Recognition with Contrastive Predictive Codingcited by 672
  5. 2020COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Imagescited by 264
  6. 2017Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?cited by 220
  7. 2016Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learningcited by 209
  8. 2020Can AI help in screening Viral and COVID-19 pneumonia?cited by 200
  9. 2020COVID-19 Image Data Collection: Prospective Predictions Are the Futurecited by 100
  10. 2020Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networkscited by 92
  11. 2020How Useful is Self-Supervised Pretraining for Visual Tasks?cited by 80
  12. 2020CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray imagescited by 68
  13. 2020Deep Learning COVID-19 Features on CXR using Limited Training Data Setscited by 68
  14. 2020Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learningcited by 67
  15. 2020Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19cited by 62
  16. 2020MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Modelscited by 61
  17. 2020Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural networkcited by 43
  18. 2020COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Imagescited by 34
  19. 2020COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray imagescited by 32
  20. 2020A Critic Evaluation of Methods for COVID-19 Automatic Detection from X-Ray Imagescited by 28
  21. 2020Deep Mining External Imperfect Data for Chest X-ray Disease Screeningcited by 27
  22. 2020Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-rayscited by 21
  23. 2020Improving performance of CNN to predict likelihood of COVID-19 using chest X-ray images with preprocessing algorithmscited by 14
  24. 2020AIforCOVID: predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre studycited by 13
  25. 2020Computer Vision For COVID-19 Control: A Surveycited by 9
  26. 20204S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detectioncited by 8
  27. 2020GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rayscited by 6
  28. 2020Medical Imaging and Computational Image Analysis in COVID-19 Diagnosis: A Reviewcited by 3
  29. 2020DRR4Covid: Learning Automated COVID-19 Infection Segmentation from Digitally Reconstructed Radiographscited by 2

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 6; 2023: 7; 2024: 2.

16 papers.

Sort:

  1. 2021Joint Learning of Localized Representations from Medical Images and Reportscited by 81
  2. 2023Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rayscited by 12
  3. 2023A Review of Predictive and Contrastive Self-supervised Learning for Medical Imagescited by 10
  4. 2023I-AI: A Controllable & Interpretable AI System for Decoding Radiologists' Intense Focus for Accurate CXR Diagnosescited by 10
  5. 2022Prior Knowledge-Guided Attention in Self-Supervised Vision Transformerscited by 7
  6. 2024Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer Approachcited by 5
  7. 2022Can we Adopt Self-supervised Pretraining for Chest X-Rays?cited by 4
  8. 2022Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rayscited by 3
  9. 2023DINO-CXR: A self supervised method based on vision transformer for chest X-ray classificationcited by 3
  10. 2022Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosiscited by 2
  11. 2023A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Imagescited by 2
  12. 2023Self-Supervised Curricular Deep Learning for Chest X-Ray Image Classificationcited by 1
4 more
  1. 2023Generalized Cross-domain Multi-label Few-shot Learning for Chest X-rayscited by 1
  2. 2024Zero-Shot Pediatric Tuberculosis Detection in Chest X-Rays using Self-Supervised Learningcited by 1
  3. 2022Contrastive Image Synthesis and Self-supervised Feature Adaptation for Cross-Modality Biomedical Image Segmentationcited by 0
  4. 2022Auto-outlier Fusion Technique for Chest X-ray classification with Multi-head Attention Mechanismcited by 0