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Updated: May 7, 2026

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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Published on: December 19, 2020

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COVLIAS 3.0:基于云的量子化混合UNet3+深度学习,用于肺部计算机断层扫描中的COVID-19病变检测

Sushant Agarwal1,2, Sanjay Saxena3, Alessandro Carriero4

  • 1Advanced Knowledge Engineering Center, GBTI, Roseville, CA, United States.

Frontiers in artificial intelligence
|July 15, 2024
PubMed
概括

这项研究引入了混合深度学习 (HDL) 模型,用于在CT扫描中改进COVID-19检测,优于传统方法. 这些模型提高了病变检测的准确性,并通过定量化提供了显著的尺寸缩小.

关键词:
冠状病毒病变的病变.在 COVID-19 疫情中,计算机断层扫描 (CT) 是一种计算机断层扫描.玻璃地面的不透明度混合深度学习是混合深度学习.定量化定量化是什么细分化 细分化的细分化

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