{"id":1073,"date":"2020-10-13T18:14:08","date_gmt":"2020-10-13T16:14:08","guid":{"rendered":"http:\/\/www.imagenglab.com\/newsite\/?page_id=1073"},"modified":"2021-10-18T23:54:59","modified_gmt":"2021-10-18T21:54:59","slug":"covid-19","status":"publish","type":"page","link":"https:\/\/www.imagenglab.com\/newsite\/covid-19\/","title":{"rendered":"COVID-19"},"content":{"rendered":"\n

IMPORTANT: ON SEPTEMBER 2021 THE ARCHIVE WAS ENRICHED WITH 31 NEW PATIENTS AND ICU INFORMATION.<\/span><\/strong><\/p>\n\n\n\n

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From this webpage it is possible downloading COVID-19 CT dataset describerd at

“<\/em>Zaffino P, Marzullo A, Moccia S, Calimeri F, De Momi E, Bertucci B, Arcuri PP, Spadea MF.<\/em>
An Open-Source COVID-19 CT Dataset with Automatic Lung Tissue Classification for Radiomics.<\/em>
Bioengineering<\/em>. 2021; 8(2):26<\/em><\/a>“.<\/em>
https:\/\/doi.org\/10.3390\/bioengineering8020026<\/em>.

Please cite this paper if you use the dataset.

The dataset is made of 93 submillimetric CTs from 81 COVID-19 positive patients. Automatic lung tissue classification, clinical score, and intensive care unit information are provided as well.
Code for experiment reproducibility and for new CT labeling is available at this GitHub repository<\/a>.<\/p>\n\n\n\n

A dedicated extension<\/a> for 3D Slicer<\/a> suite was implemented to automatically label lung tissues of a COVID-19 positive patient’s CT. This tool can be easily installed by using the dedicated extension manager.

ATTENTION:<\/span><\/strong> the dataset is provided under NON commercial licence CC BY-NC 4.0<\/a>.<\/p>\n\n\n\n

For practical reasons, patients are listed both as single folders and grouped in zip files. However, the volumes are the same.<\/p>\n\n\n\n

An xlsx document contains additional information about the dataset. <\/p>\n\n\n\n

For any question please write to
p.zaffino @at@ unicz.it<\/p>\n\n\n

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