论文标题
胸部X射线图像的深度学习分类
Deep learning classification of chest x-ray images
论文作者
论文摘要
我们提出了一种基于深度学习的方法，用于分类胸部X射线图像中常见的病理。大量可公开的胸部X射线图像提供了成功采用深度学习方法来减少胸部疾病的误诊所必需的数据。我们将方法应用于两种示例病理学，肺结核和心脏肿大的分类，并将方法的性能与三种现有方法进行了比较。结果表明，与现有方法相比，AUC检测结节和心脏肿大的改善。
We propose a deep learning based method for classification of commonly occurring pathologies in chest X-ray images. The vast number of publicly available chest X-ray images provides the data necessary for successfully employing deep learning methodologies to reduce the misdiagnosis of thoracic diseases. We applied our method to the classification of two example pathologies, pulmonary nodules and cardiomegaly, and we compared the performance of our method to three existing methods. The results show an improvement in AUC for detection of nodules and cardiomegaly compared to the existing methods.
