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Updated: Jul 12, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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联合分类和细分,以便通过胸部X射线对急性呼吸困扰综合征进行可解释的诊断

Mohammad Yahyatabar1, Philippe Jouvet2, Farida Cheriet1

  • 1Polytechnique Montréal, Department of Computer and Software Engineering, Montreal, Quebec, Canada.

Journal of medical imaging (Bellingham, Wash.)
|October 19, 2023
PubMed
概括

这项研究介绍了Dense-Ynet,这是一个可解释的深度学习模型,用于从胸部X射线中诊断急性呼吸困扰综合征 (ARDS). 该模型在检测ARDS症状方面实现了高精度,改善了临床决策.

关键词:
急性呼吸困扰综合征.急性呼吸困扰综合征.这是分类分类的分类.计算机辅助诊断是指计算机辅助的诊断.深度学习是一种深度学习.细分化 细分化的细分化图像X射线图像的图像X射线图像的图像

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