作者
Shokouh Shakouri, Mohammad Amin Bakhshali, Parvaneh Layegh, Behzad Kiani, Farid Masoumi, Saeedeh Ataei Nakhaei, Sayyed Mostafa Mostafavi
发表日期
2021/5/12
期刊
BMC research notes
卷号
14
期号
1
页码范围
178
出版商
BioMed Central
简介
Objectives
The ongoing Coronavirus disease 2019 (COVID-19) pandemic has drastically impacted the global health and economy. Computed tomography (CT) is the prime imaging modality for diagnosis of lung infections in COVID-19 patients. Data-driven and Artificial intelligence (AI)-powered solutions for automatic processing of CT images predominantly rely on large-scale, heterogeneous datasets. Owing to privacy and data availability issues, open-access and publicly available COVID-19 CT datasets are difficult to obtain, thus limiting the development of AI-enabled automatic diagnostic solutions. To tackle this problem, large CT image datasets encompassing diverse patterns of lung infections are in high demand.
Data description
In the present study, we provide an open-source repository containing 1000+ CT images of COVID-19 lung infections established by a team of board-certified radiologists. CT images …
引用总数
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