The MIMIC-CXR Database

The current version of the MIMIC-CXR Database is v1.0 (22 January, 2019).

This database is described in

Johnson AEW, Pollard TJ, Berkowitz S, Greenbaum NR, Lungren MP, Deng C-Y, Mark RG, Horng S. MIMIC-CXR: A large publicly available database of labeled chest radiographs. arXiv (2019).

Please cite this publication when referencing this material, and also include the standard citation for PhysioNet:

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220 [Circulation Electronic Pages; http://circ.ahajournals.org/content/101/23/e215.full]; 2000 (June 13).

MIMIC-CXR is a large, publicly-available database comprising of de-identified chest radiographs from patients admitted to the Beth Israel Deaconess Medical Center between 2011 and 2016. The dataset contains 371,920 chest x-rays associated with 227,943 imaging studies. 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 a wide range of research in medical computer vision.

The MIMIC-CXR Database, although de-identified, still contains detailed information regarding the clinical care of patients, and must be treated with appropriate care and respect. Researchers seeking to use the full Clinical Database must formally request access. Please see the instructions for getting access to the MIMIC-III Database - the process is the same for MIMIC-CXR.

Researchers who have received access to MIMIC-CXR can download the data on PhysioNetWorks: MIMIC-CXR Database.

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Updated Ĩetrtek, 24 januar 2019 at 23:17 CET

PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.