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RAIG COVID19 compiled dataset.zip

Version 4 2021-05-11, 12:40
Version 3 2021-04-20, 14:47
Version 2 2021-03-03, 09:25
Version 1 2021-03-03, 08:55
dataset
posted on 2021-05-11, 12:40 authored by Michael FayemiwoMichael Fayemiwo, Toluwase Olowookere, Samson Arekete, Adewale Ogunde, Mba Odim, Bosede Oguntunde, Oluwabunmi Olaniyan, Theresa Ojewumi, Idowu Oyetade, Ademola Aremu, Aderonke Kayode
Chest X-ray images were selected from a database of chest X-ray images for COVID-19 positive cases along with normal and viral pneumonia images which were collated by researchers from Qatar University and the University of Dhaka along with collaborators from Pakistan and Malaysia and some medical doctors. In their current release, there are 219 COVID-19 positive images, 1341 normal images and 1345 viral pneumonia images (Chowdhury et al., 2020). To ensure multiple representations, the dataset of chest X-ray images for both COVID-19 and normal cases were also selected from Mendeley dataset repository (El-Shafai, 2020) which contains 5500 Non-COVID X-ray images and 4044 COVID-19 X-ray images. This study, therefore, adopted these multi source datasets. Due to limited computing resources, in this study, 1,300 images were selected from each category. That is, 1,300 images of COVID-19 positive cases, 1,300 Normal images and 1,300 images of viral pneumonia cases, totaling 3,900 images in all. It is noted here that further descriptions of the datasets were not provided by the authors of the sources of the datasets.

El-Shafai, Walid; Abd El-Samie, Fathi (2020), “Extensive COVID-19 X-Ray and CT Chest Images Dataset”, Mendeley Data, V3, doi: 10.17632/8h65ywd2jr.3

Chowdhury, M. E., Rahman, T., Khandakar, A., Mazhar, R., Kadir, M. A., Mahbub, Z. B., . . . Reaz, M. B. (2020, March 29). Can AI help in screening Viral and COVID-19 pneumonia? Retrieved from https://arxiv.org/abs/2003.13145; https://www.kaggle.com/tawsifurrahman/covid19-radiography-database

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