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Updated: Jun 11, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
08:05

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Published on: December 19, 2020

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深度COVIDNet-CXR:在增强的胸部X射线上识别COVID-19的深度学习策略

Gokhan Altan1, Süleyman Serhan Narli1

  • 1Computer Engineering Department, Iskenderun Technical University, Hatay, Türkiye.

Biomedizinische Technik. Biomedical engineering
|October 7, 2024
PubMed
概括

这项研究使用自适应组图平衡 (AHE) 和ConvNet模型增强了胸部X射线的COVID-19检测. VGG16显示出强烈的概括性,在识别COVID-19的大数据集上实现了95.04%的准确性.

关键词:
在 COVID-19 疫情中,这就是ConvNet的意义.适应性直方体平衡等同化胸部X射线 胸部X射线 胸部X射线深度学习是一种深度学习.转移学习转移学习

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