mlsanityData to 14 Oct 2026

Multi Source COVID-19 Detection via Kernel-Density-based Slice Sampling

arXiv 2507.01564 ↗First posted 2 Jul 2025eess.IV cs.CVcited by 1

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Abstract (arXiv)

We present our solution for the Multi-Source COVID-19 Detection Challenge, which classifies chest CT scans from four distinct medical centers. To address multi-source variability, we employ the Spatial-Slice Feature Learning (SSFL) framework with Kernel-Density-based Slice Sampling (KDS). Our preprocessing pipeline combines lung region extraction, quality control, and adaptive slice sampling to select eight representative slices per scan. We compare EfficientNet and Swin Transformer architectures on the validation set. The EfficientNet model achieves an F1-score of 94.68%, compared to the Swin Transformer's 93.34%. The results demonstrate the effectiveness of our KDS-based pipeline on multi-source data and highlight the importance of dataset balance in multi-institutional medical imaging evaluation.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 20 references that are in the map. First posted on arXiv 2 Jul 2025.

Builds on

11 of 20 references.

References · 11

  1. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  2. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  3. 2020Deep Transparent Prediction through Latent Representation Analysiscited by 72
  4. 2021MIA-COV19D: COVID-19 Detection through 3-D Chest CT Image Analysiscited by 72
  5. 2023A Deep Neural Architecture for Harmonizing 3-D Input Data Analysis and Decision Making in Medical Imagingcited by 39
  6. 2024Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scanscited by 30
  7. 2024COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI Systemcited by 23
  8. 2024SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detectioncited by 14
  9. 2023Strong Baseline and Bag of Tricks for COVID-19 Detection of CT Scanscited by 4
  10. 2024A Closer Look at Spatial-Slice Features Learning for COVID-19 Detectioncited by 3
  11. 2024Simple 2D Convolutional Neural Network-based Approach for COVID-19 Detectioncited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisationcited by 0