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MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic
Author(s) -
С. П. Морозов,
Anna Andreychenko,
Ivan A. Blokhin,
Pavel Gelezhe,
А. P. Gonchar,
А. Е. Николаев,
Nikolay Pavlov,
Valeria Chernina,
Victor А. Gombolevskiy
Publication year - 2020
Publication title -
digital diagnostics
Language(s) - English
Resource type - Journals
eISSN - 2712-8962
pISSN - 2712-8490
DOI - 10.17816/dd46826
Subject(s) - covid-19 , computer science , computed tomography , artificial intelligence , tomography , pixel , image quality , consolidation (business) , medical physics , data mining , medicine , radiology , image (mathematics) , pathology , disease , outbreak , infectious disease (medical specialty) , accounting , business
With the ongoing COVID-19 pandemic decreasing availability of polymerase chain reaction with reverse transcription and the snowballing growth of medical imaging, especially the number of chest computed tomography (CT) scans being performed, methods to augment and automate the image analysis, increasing productivity and minimizing human error are of particular importance. The creation of high-quality datasets is essential for the development and validation of artificial intelligence algorithms. Such technologies have sufficient accuracy in diagnosing COVID-19 in medical imaging. The presented large-scale dataset contains anonymized human CT scans with COVID-19 features as well as normal studies. Some studies were tagged by radiologists using binary pixel masks of regions of interest (e.g., characteristic areas of consolidation and ground-glass opacities). CT data were acquired between March 1, 2020, and April 25, 2020, and provided by municipal hospitals in Moscow, Russia. The presented dataset is licensed under Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0).

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