论文标题
使用注意力模型进行MRI扫描的放射学报告（警报）自动标记
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
论文作者
论文摘要
为培训大容量神经网络的大型数据集标记是开发基于深度学习的医学成像应用程序的主要障碍。在这里，我们提出了一个基于变压器的网络用于磁共振成像（MRI）放射学报告分类，该网络通过根据自由文本专家放射学报告来分配图像标签来自动化此任务。我们的模型的表现与专家放射科医生的表现相当，并且比专家医生的表现更好，证明了这种方法的可行性。我们在线提供代码，供研究人员标记自己的MRI数据集用于医学成像应用程序。
Labelling large datasets for training high-capacity neural networks is a major obstacle to the development of deep learning-based medical imaging applications. Here we present a transformer-based network for magnetic resonance imaging (MRI) radiology report classification which automates this task by assigning image labels on the basis of free-text expert radiology reports. Our model's performance is comparable to that of an expert radiologist, and better than that of an expert physician, demonstrating the feasibility of this approach. We make code available online for researchers to label their own MRI datasets for medical imaging applications.
