MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic

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Abstract

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).

About the authors

Sergey P. Morozov

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: morozov@npcmr.ru
ORCID iD: 0000-0001-6545-6170
SPIN-code: 8542-1720

MD, PhD, Professor

Russian Federation, Moscow

Anna E. Andreychenko

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: a.andreychenko@npcmr.ru
ORCID iD: 0000-0001-6359-0763
SPIN-code: 6625-4186

MD

Russian Federation, Moscow

Ivan A. Blokhin

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: i.blokhin@npcmr.ru
ORCID iD: 0000-0002-2681-9378
SPIN-code: 3306-1387

MD

Russian Federation, Moscow

Pavel B. Gelezhe

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: gelezhe.pavel@gmail.com
ORCID iD: 0000-0003-1072-2202
SPIN-code: 4841-3234

MD, PhD

Russian Federation, Moscow

Anna P. Gonchar

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: a.gonchar@npcmr.ru
ORCID iD: 0000-0001-5161-6540
SPIN-code: 3513-9531

MD

Russian Federation, Moscow

Alexander E. Nikolaev

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: a.e.nikolaev@yandex.ru
ORCID iD: 0000-0001-5151-4579
SPIN-code: 1320-1651

MD

Russian Federation, Moscow

Nikolay A. Pavlov

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: n.pavlov@npcmr.ru
ORCID iD: 0000-0002-4309-1868
SPIN-code: 9960-4160

MD, MPA

Russian Federation, Moscow

Valeria Yu. Chernina

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Email: v.chernina@npcmr.ru
ORCID iD: 0000-0002-0302-293X
SPIN-code: 8896-8051

MD

Russian Federation, Moscow

Victor A. Gombolevskiy

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow

Author for correspondence.
Email: g_victor@mail.ru
ORCID iD: 0000-0003-1816-1315
SPIN-code: 6810-3279

MD, PhD, MPH

Russian Federation, Moscow

References

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Supplementary files

Supplementary Files
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2. Figure 1: The order of forming a dataset.

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3. Figure 2: Examples of chest CT scans of patients with varying degrees of COVID-19 severity. Left to right, upper row: axial CT slices of patients with COVID-19 from mild (CT-1) to critical (CT-4) severity. Left to right, lower row: same CT data after tagging.

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4. Figure 3: Data storage structure in the dataset.

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Copyright (c) 2020 Morozov S.P., Andreychenko A.E., Blokhin I.A., Gelezhe P.B., Gonchar A.P., Nikolaev A.E., Pavlov N.A., Chernina V.Y., Gombolevskiy V.A.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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