Enviar artigo por via de e-mail MosMedData: data set of 1110 chest CT scans performed during the COVID-19 epidemic
- Autores: Morozov S.1, Andreychenko A.1, Blokhin I.1, Gelezhe P.1, Gonchar A.1, Nikolaev A.1, Pavlov N.1, Chernina V.1, Gombolevskiy V.1
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Afiliações:
- Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow
- Edição: Volume 1, Nº 1 (2020)
- Páginas: 49-59
- Seção: Datasets
- URL: https://journals.rcsi.science/DD/article/view/46826
- DOI: https://doi.org/10.17816/DD46826
- ID: 46826
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Resumo
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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##article.viewOnOriginalSite##Sobre autores
Sergey 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
Código SPIN: 8542-1720
MD, PhD, Professor
Rússia, MoscowAnna 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
Código SPIN: 6625-4186
MD
Rússia, MoscowIvan 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
Código SPIN: 3306-1387
MD
Rússia, MoscowPavel 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
Código SPIN: 4841-3234
MD, PhD
Rússia, MoscowAnna 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
Código SPIN: 3513-9531
MD
Rússia, MoscowAlexander 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
Código SPIN: 1320-1651
MD
Rússia, MoscowNikolay 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
Código SPIN: 9960-4160
MD, MPA
Rússia, MoscowValeria 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
Código SPIN: 8896-8051
MD
Rússia, MoscowVictor Gombolevskiy
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow
Autor responsável pela correspondência
Email: g_victor@mail.ru
ORCID ID: 0000-0003-1816-1315
Código SPIN: 6810-3279
MD, PhD, MPH
Rússia, MoscowBibliografia
- Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in Coronavirus Disease 2019 (COVID19) in China: a report of 1014 cases. Radiology. 2020;296(2):E32–E40. doi: 10.1148/radiol.2020200642
- Handbook of COVID-19 Prevention and Treatment. Ed. by T. Liang. Zhejiang University School of Medicine; 2020. 68 p.
- Huang Z, Zhao S, Li Z, et al. The battle against Coronavirus Disease 2019 (COVID-19): emergency management and infection control in a Radiology Department. J Am Coll Radiol. 2020;17(6):710–716. doi: 10.1016/j.jacr.2020.03.011
- Morozov SP, Gombolevskiy VA, Cherninа VY, et al. Prediction of lethal outcomes in COVID-19 cases based on the results chest computed tomography. Tuberculosis and Lung Diseases. 2020;98(6):7–14. (In Russ.) doi: 10.21292/2075-1230-2020-98-6-7-14
- Morozov S, Guseva E, Ledikhova N, et al. Telemedicine-based system for quality management and peer review in radiology. Insights Imaging. 2018;9(3):337–341. doi: 10.1007/s13244-018-0629-y
- Li L, Qin L, Xu Z, et al. Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT: evaluation of the diagnostic accuracy. Radiology. 2020;296(2):E65–E71. doi: 10.1148/radiol.2020200905
- Ucar F, Korkmaz D. COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images. Med Hypotheses. 2020;140:109761. doi: 10.1016/j.mehy.2020.109761
- Vremennye metodicheskie rekomendatsii “Profilaktika, diagnostika i lechenie novoi koronavirusnoi infektsii (COVID-19). Versiya 9” (utv. Ministerstvom zdravookhraneniya RF 26 oktyabrya 2020). Available from: https://base.garant.ru/74810808/
- Morozov SP, Protsenko DN, Smetanina SV, editors. Radiation diagnostics of coronavirus disease (COVID-19): organization, methodology, interpretation of results: guidelines. Series “Best practices of radiation and instrumental diagnostics”. Issue 65. Moscow; 2020.
- Morozov SP, Vladzymyrskyy AV, Klyashtornyy VG, et al. Clinical acceptance of software based on artificial intelligence technologies (radiology). Series “Best practices in medical imaging”. Moscow; 2019. Issue 57.
- Cohen JP, Morrison P, Dao L. COVID-19 Image Data Collection [Internet]. 2020 [cited 2020 Mar 25]. Available from: https://arxiv.org/abs/2003.11597
- Jun M, Cheng G, Yixin W, et al. COVID-19 CT lung and infection segmentation dataset. Verson 1.0. 2020. doi: 10.5281/zenodo.3757476
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