Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation. With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers. However, a key challenge in the development of these techniques is the lack of sufficient data. Here we describe MIMIC-CXR, a large dataset of 371,920 chest x-rays associated with 227,943 imaging studies sourced from the Beth Israel Deaconess Medical Center between 2011 - 2016. Each imaging study can pertain to one or more images, but most often are associated with two images: a frontal view and a lateral view. Images are provided with 14 labels derived from a natural language processing tool applied to the corresponding free-text radiology reports. All images have been de-identified to protect patient privacy. The dataset is made freely available to facilitate and encourage wide range of research in medical computer vision.

该论文介绍了MIMIC-CXR-JPG v2.0.0数据集，这是一个从2011年至2016年收集的大型数据集，包括377,110个胸部X光片，提供了14个标签，旨在为医学计算机视觉领域提供数据和标准。

MIMIC-CXR-JPG：一个大型公开可用的带标签胸部X射线数据库