mlsanityData to 7 Oct 2026

Explainability Guided Multi-Site COVID-19 CT Classification

arXiv 2103.13677 ↗First posted 25 Mar 2021eess.IV cs.CV cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

Radiologist examination of chest CT is an effective way for screening COVID-19 cases. In this work, we overcome three challenges in the automation of this process: (i) the limited number of supervised positive cases, (ii) the lack of region-based supervision, and (iii) the variability across acquisition sites. These challenges are met by incorporating a recent augmentation solution called SnapMix, by a new patch embedding technique, and by performing a test-time stability analysis. The three techniques are complementary and are all based on utilizing the heatmaps produced by the Class Activation Mapping (CAM) explainability method. Compared to the current state of the art, we obtain an increase of five percent in the F1 score on a site with a relatively high number of cases, and a gap twice as large for a site with much fewer training images.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 35 of its 45 references that are in the map. First posted on arXiv 25 Mar 2021.

Builds on

35 of 45 references.

References · 35

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  3. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  4. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
  5. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  6. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  7. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  8. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,875
  9. 2015Learning Deep Features for Discriminative Localizationcited by 2,430
  10. 2016Identity Mappings in Deep Residual Networkscited by 1,960
  11. 2018Unsupervised Feature Learning via Non-Parametric Instance-level Discriminationcited by 1,838
  12. 2017Learning Important Features Through Propagating Activation Differencescited by 1,454
23 more
  1. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,182
  2. 2017Learning Transferable Architectures for Scalable Image Recognitioncited by 1,097
  3. 2019Self-Supervised Learning of Pretext-Invariant Representationscited by 806
  4. 2017Interpretable Explanations of Black Boxes by Meaningful Perturbationcited by 611
  5. 2017Learning multiple visual domains with residual adapterscited by 553
  6. 2020COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Imagescited by 264
  7. 2019Understanding Deep Networks via Extremal Perturbations and Smooth Maskscited by 257
  8. 2019Full-Gradient Representation for Neural Network Visualizationcited by 189
  9. 2018Tell Me Where to Look: Guided Attention Inference Networkcited by 168
  10. 2018Efficient parametrization of multi-domain deep neural networkscited by 168
  11. 2018MixUp as Locally Linear Out-Of-Manifold Regularizationcited by 158
  12. 2020MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Datacited by 121
  13. 2020COVID-CT-Dataset: A CT Scan Dataset about COVID-19cited by 93
  14. 2020SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Datacited by 56
  15. 2019Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networkscited by 49
  16. 2020COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest CT Imagescited by 39
  17. 2020Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysiscited by 38
  18. 2017Improving Deep Learning using Generic Data Augmentationcited by 36
  19. 2020Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorizationcited by 23
  20. 2020Contrastive Cross-site Learning with Redesigned Net for COVID-19 CT Classificationcited by 22
  21. 2015Deep Image: Scaling up Image Recognitioncited by 16
  22. 2020Finding Covid-19 from Chest X-rays using Deep Learning on a Small Datasetcited by 16
  23. 2020Extracting possibly representative COVID-19 Biomarkers from X-Ray images with Deep Learning approach and image data related to Pulmonary Diseasescited by 13

Built on by

Not cited yet.