mlsanityData to 7 Oct 2026

Advancing COVID-19 Detection in 3D CT Scans

arXiv 2403.11953 ↗First posted 18 Mar 2024eess.IV cs.CVcited by 5

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Abstract (arXiv)

To make a more accurate diagnosis of COVID-19, we propose a straightforward yet effective model. Firstly, we analyse the characteristics of 3D CT scans and remove the non-lung parts, facilitating the model to focus on lesion-related areas and reducing computational cost. We use ResNeSt50 as the strong feature extractor, initializing it with pretrained weights which have COVID-19-specific prior knowledge. Our model achieves a Macro F1 Score of 0.94 on the validation set of the 4th COV19D Competition Challenge I, surpassing the baseline by 16%. This indicates its effectiveness in distinguishing between COVID-19 and non-COVID-19 cases, making it a robust method for COVID-19 detection.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 17 of its 39 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

17 of 39 references.

References · 17

  1. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  2. 2017Quo Vadis, Action Recognition? A New Model and the Kinetics Datasetcited by 3,259
  3. 2022Visual Prompt Tuningcited by 1,674
  4. 2021An Empirical Study of Training Self-Supervised Vision Transformerscited by 1,610
  5. 2017ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseasescited by 969
  6. 2018Exploring the Limits of Weakly Supervised Pretrainingcited by 604
  7. 2020ResNeSt: Split-Attention Networkscited by 445
  8. 2018Efficient parametrization of multi-domain deep neural networkscited by 168
  9. 2020Deep Transparent Prediction through Latent Representation Analysiscited by 72
  10. 2021MIA-COV19D: COVID-19 Detection through 3-D Chest CT Image Analysiscited by 72
  11. 2023Text-guided Foundation Model Adaptation for Pathological Image Classificationcited by 47
  12. 2023A Deep Neural Architecture for Harmonizing 3-D Input Data Analysis and Decision Making in Medical Imagingcited by 39
5 more
  1. 2024Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scanscited by 30
  2. 2023MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Datasetcited by 25
  3. 2022CMC v2: Towards More Accurate COVID-19 Detection with Discriminative Video Priorscited by 7
  4. 2022Boosting COVID-19 Severity Detection with Infection-aware Contrastive Mixup Classificationcited by 7
  5. 2023Strong Baseline and Bag of Tricks for COVID-19 Detection of CT Scanscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Multi-Source COVID-19 Detection via Variance Risk Extrapolationcited by 5
  2. 2025Advancing Lung Disease Diagnosis in 3D CT Scanscited by 4
  3. 2026Clinical Priors Guided Lung Disease Detection in 3D CT Scanscited by 0
  4. 2026Vision-Language Model Based Multi-Expert Fusion for CT Image Classificationcited by 0
  5. 2026Robust Multi-Source Covid-19 Detection in CT Imagescited by 0