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MIMIC-CXR,一个去标识化的、公开可用的、包含自由文本报告的胸部 X 光数据库。

MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports.

机构信息

Institute of Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA.

Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA, USA.

出版信息

Sci Data. 2019 Dec 12;6(1):317. doi: 10.1038/s41597-019-0322-0.

Abstract

Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's chest, but requires 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. Here we describe MIMIC-CXR, a large dataset of 227,835 imaging studies for 65,379 patients presenting to the Beth Israel Deaconess Medical Center Emergency Department between 2011-2016. Each imaging study can contain one or more images, usually a frontal view and a lateral view. A total of 377,110 images are available in the dataset. Studies are made available with a semi-structured free-text radiology report that describes the radiological findings of the images, written by a practicing radiologist contemporaneously during routine clinical care. All images and reports have been de-identified to protect patient privacy. The dataset is made freely available to facilitate and encourage a wide range of research in computer vision, natural language processing, and clinical data mining.

摘要

胸部 X 光摄影是一种非常强大的成像方式,可以对患者的胸部进行详细检查,但需要专门的培训才能进行正确的解读。随着高性能通用计算机视觉算法的出现,对胸部 X 光片进行准确的自动分析越来越受到研究人员的关注。这里我们描述了 MIMIC-CXR,这是一个包含 227835 个成像研究和 65379 名患者的大型数据集,这些患者于 2011 年至 2016 年期间在 Beth Israel Deaconess 医疗中心急诊科就诊。每个成像研究都可以包含一个或多个图像,通常是正面视图和侧面视图。该数据集共有 377110 张图像。研究采用半结构化的自由文本放射报告提供,该报告由在常规临床护理期间的执业放射科医生描述图像的放射学发现。所有图像和报告都已进行去识别处理,以保护患者隐私。该数据集免费提供,以促进和鼓励计算机视觉、自然语言处理和临床数据挖掘方面的广泛研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/95ec/6908718/bd3de284c9be/41597_2019_322_Fig1_HTML.jpg

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