论文标题
检测医学图像中的快捷方式 - 胸部X射线案例研究
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays
论文作者
论文摘要
大型公共数据集的可用性以及计算能力的增加已将医学界的兴趣转移到高性能算法上。但是，很少关注数据质量及其注释。可以报告基准数据集上的高性能，而无需考虑数据中可能的捷径或工件，此外，模型未在亚种群组上测试。通过这项工作，我们旨在提高人们对捷径问题的认识。我们验证了以前的发现，并使用两个公开可用的数据集介绍了有关胸部X射线检查的案例研究。我们共享带排水沟的气胸图像子集的注释。我们以医学图像分类的一般建议结束。
The availability of large public datasets and the increased amount of computing power have shifted the interest of the medical community to high-performance algorithms. However, little attention is paid to the quality of the data and their annotations. High performance on benchmark datasets may be reported without considering possible shortcuts or artifacts in the data, besides, models are not tested on subpopulation groups. With this work, we aim to raise awareness about shortcuts problems. We validate previous findings, and present a case study on chest X-rays using two publicly available datasets. We share annotations for a subset of pneumothorax images with drains. We conclude with general recommendations for medical image classification.
