论文标题
利用基于深度学习的方法的智能手机捕获射线照相的解释
Interpretation of smartphone-captured radiographs utilizing a deep learning-based approach
论文作者
论文摘要
最近，可以自动自动解释医学图像的计算机辅助诊断系统（CADS）是最近学术关注的新兴主题。对于X光片，已经开发了几种基于学习的系统或模型来研究多标签疾病识别任务。但是，他们都没有经过培训来从事智能手机捕获的胸部X光片。在这项研究中，我们提出了一个系统，该系统包括一系列基于深度学习的神经网络，该网络在新发布的Chexphoto数据集中训练以解决此问题。提出的方法在AUC中获得了0.684的有希望的结果，平均F1得分为0.699。据我们所知，这是第一项发表的研究，该研究表明能够处理智能手机捕获的X光片。
Recently, computer-aided diagnostic systems (CADs) that could automatically interpret medical images effectively have been the emerging subject of recent academic attention. For radiographs, several deep learning-based systems or models have been developed to study the multi-label diseases recognition tasks. However, none of them have been trained to work on smartphone-captured chest radiographs. In this study, we proposed a system that comprises a sequence of deep learning-based neural networks trained on the newly released CheXphoto dataset to tackle this issue. The proposed approach achieved promising results of 0.684 in AUC and 0.699 in average F1 score. To the best of our knowledge, this is the first published study that showed to be capable of processing smartphone-captured radiographs.
