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Deep-Learning-Assisted Highly-Accurate COVID-19 Diagnosis on Lung Computed Tomography Images

arXiv 2507.04252 ↗First posted 6 Jul 2025eess.IV cs.AI cs.CVcited by 0

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Abstract (arXiv)

COVID-19 is a severe and acute viral disease that can cause symptoms consistent with pneumonia in which inflammation is caused in the alveolous regions of the lungs leading to a build-up of fluid and breathing difficulties. Thus, the diagnosis of COVID using CT scans has been effective in assisting with RT-PCR diagnosis and severity classifications. In this paper, we proposed a new data quality control pipeline to refine the quality of CT images based on GAN and sliding windows. Also, we use class-sensitive cost functions including Label Distribution Aware Loss(LDAM Loss) and Class-balanced(CB) Loss to solve the long-tail problem existing in datasets. Our model reaches more than 0.983 MCC in the benchmark test dataset.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 22 references that are in the map. First posted on arXiv 6 Jul 2025.

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References · 11

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2017Improved Training of Wasserstein GANscited by 2,235
  3. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,054
  4. 2019Class-Balanced Loss Based on Effective Number of Samplescited by 1,245
  5. 2019Learning Imbalanced Datasets with Label-Distribution-Aware Margin Losscited by 989
  6. 2017Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discoverycited by 566
  7. 2020Calibrating Deep Neural Networks using Focal Losscited by 357
  8. 2015Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networkscited by 214
  9. 2020MosMedData: Chest CT Scans With COVID-19 Related Findings Datasetcited by 104
  10. 2019MisGAN: Learning from Incomplete Data with Generative Adversarial Networkscited by 75
  11. 2020STAN-CT: Standardizing CT Image using Generative Adversarial Networkcited by 11

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