mlsanityData to 7 Oct 2026

A Closer Look at Spatial-Slice Features Learning for COVID-19 Detection

arXiv 2404.01643 ↗First posted 2 Apr 2024eess.IV cs.CV cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

Conventional Computed Tomography (CT) imaging recognition faces two significant challenges: (1) There is often considerable variability in the resolution and size of each CT scan, necessitating strict requirements for the input size and adaptability of models. (2) CT-scan contains large number of out-of-distribution (OOD) slices. The crucial features may only be present in specific spatial regions and slices of the entire CT scan. How can we effectively figure out where these are located? To deal with this, we introduce an enhanced Spatial-Slice Feature Learning (SSFL++) framework specifically designed for CT scan. It aim to filter out a OOD data within whole CT scan, enabling our to select crucial spatial-slice for analysis by reducing 70% redundancy totally. Meanwhile, we proposed Kernel-Density-based slice Sampling (KDS) method to improve the stability when training and inference stage, therefore speeding up the rate of convergence and boosting performance. As a result, the experiments demonstrate the promising performance of our model using a simple EfficientNet-2D (E2D) model, even with only 1% of the training data. The efficacy of our approach has been validated on the COVID-19-CT-DB datasets provided by the DEF-AI-MIA workshop, in conjunction with CVPR 2024. Our source code is available at https://github.com/ming053l/E2D

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 29 of its 67 references that are in the map. First posted on arXiv 2 Apr 2024.

Builds on

29 of 67 references.

References · 29

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17 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Taming Domain Shift in Multi-source CT-Scan Classification via Input-Space Standardizationcited by 2
  2. 2025Multi Source COVID-19 Detection via Kernel-Density-based Slice Samplingcited by 1
  3. 2026Robust Multi-Source Covid-19 Detection in CT Imagescited by 0