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AI models for COVID-19 CT scan classification show promising results · 2 papers

By PulseAugur Editorial · [2 sources] ·

Two research papers submitted to arXiv propose novel methods for classifying COVID-19 cases from chest CT scans. The first paper introduces a hybrid 2D/3D Convolutional Neural Network (CNN) that extracts features from multiple planes within CT volumes, achieving 83.3% accuracy on a dataset of 1288 scans. The second paper presents a hybrid model combining a 3D CNN with a 3D MLP-Mixer, which leverages Vision Transformer-like architecture to capture both local and global image features, reaching 79.5% accuracy on a dataset of 1205 scans. Both methods aim to assist in the rapid diagnosis of COVID-19 and alleviate manpower shortages in medical institutions. AI

IMPACT These AI models could accelerate COVID-19 diagnosis and reduce strain on medical resources.

RANK_REASON Two academic papers published on arXiv detailing new AI methods for medical image analysis.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI models for COVID-19 CT scan classification show promising results · 2 papers

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Two academic papers published on arXiv detailing new AI methods for medical image analysis.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori ·

    Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes

    arXiv:2607.28950v1 Announce Type: new Abstract: This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVID-19) spreads over the world, causing a large number of infected patients and deat…

  2. arXiv cs.CV TIER_1 English(EN) · Masahiro Oda, Tong Zheng, Yuichiro Hayashi, Yoshito Otake, Masahiro Hashimoto, Toshiaki Akashi, Shigeki Aoki, Kensaku Mori ·

    Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

    arXiv:2607.28978v1 Announce Type: new Abstract: This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-19) spreads over the world, causing a large number of infected patients and death…

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