COVID-19 & Normal CT Segmentation Dataset

This dataset includes CT data and segmentation masks from patients diagnosed with COVID-19, as well as data from subjects without the infection.

This study is approved under the ethical approval codes of IR.TUMS.IKHC.REC.1399.255 and IR.TUMS.VCR.REC.1399.488 at Tehran University of Medical Sciences.

The code for loading the dataset and running an AI model is available on:
https://github.com/SamanSotoudeh/COVID19-segmentation

Please use the following citations:

1- Arian, Arvin; Mehrabinejad, Mohammad-Mehdi; Zoorpaikar, Mostafa; Hasanzadeh, Navid; Sotoudeh-Paima, Saman; Kolahi, Shahriar; Gity, Masoumeh; Soltanian-Zadeh, "Accuracy of Artificial Intelligence CT Quantification in
Predicting COVID-19 Subjects’ Prognosis" PLoS ONE (2023).

2- Sotoudeh-Paima, Saman, et al. "A Multi-centric Evaluation of Deep Learning Models for Segmentation of COVID-19 Lung Lesions on Chest CT Scans." Iranian Journal of Radiology 19.4 (2022).

3- Hasanzadeh, Navid, et al. "Segmentation of COVID-19 Infections on CT: Comparison of four UNet-based networks." 2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME). IEEE, 2020.