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胸部X射线数据集和肺部细分的地面真相

Rima Tri Wahyuningrum¹, Indah Yunita¹, Achmad Bauravindah¹

¹Department of Informatics Engineering, Faculty of Engineering, University of Trunojoyo Madura, Indonesia.

|October 16, 2023

概括

这项研究引入了292张胸部X射线图像的验证数据集,用于人工智能开发. 这些数据有助于训练深度学习模型,通过图像细分和分类来准确检测Covid-19和肺炎.

科学领域:

医学成像和人工智能医学成像和人工智能
放射学和计算机辅助诊断技术

背景情况:

胸部X射线对于诊断Covid-19至关重要,计算机辅助分析提高了准确性.
图像细分对于早期疾病检测和医学成像中的精确诊断至关重要.
深度学习模型需要经过验证的数据集,以便有效地训练图像细分和分类任务.

研究的目的:

为人工智能驱动的医学诊断提供一个精心验证的胸部X射线图像数据集.
促进用于疾病检测和分类的先进深度学习模型的开发.

主要方法:

来自Airlangga大学医院的292张胸部X射线图像的汇编.
包含每张图像的放射学家验证的地面真相数据.
数据集将图像分类为Covid-19,肺炎和正常情况.

主要成果:

一个新的数据集,包括292张胸部X射线图像和经过验证的地面真相,现在已经可用了.
该数据集支持人工智能模型培训,用于细分和分类肺部疾病.
使用人工智能提高诊断Covid-19和肺炎的准确性.

结论:

这一数据集对于在医学图像分析中推进人工智能是有价值的.
它可以训练强大的深度学习模型来解释胸部X射线.
在临床环境中促进更准确,更有效的诊断结果.

关键词:

胸部X射线胸部X射线这就是Covid-19的原因.深度学习是一种深度学习.诊断诊断诊断诊断诊断医疗图像细分医疗图像细分

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