Convolutional Neural Network Multiclass Classification Project involving X rays of normal lungs, lungs with Pneumonia and lungs with Covid-19

Dataset obtained from Kaggle

Objective

• Researchers can use this database to produce useful and impactful scholarly work on COVID-19, which can help in tackling this pandemic.

Citation

• Please cite this database if you are using it for any scientific purpose: M.E.H. Chowdhury, T. Rahman, A. Khandakar, R. Mazhar, M.A. Kadir, Z.B. Mahbub, K.R. Islam, M.S. Khan, A. Iqbal, N. Al-Emadi, M.B.I. Reaz, M. T. Islam, “Can AI help in screening Viral and COVID-19 pneumonia?” IEEE Access, Vol. 8, 2020, pp. 132665 - 132676.

Acknowledgments Thanks to the Italian Society of Medical and Interventional Radiology (SIRM) for publicly providing the COVID-19 Chest X-Ray dataset [1] and would like to thank J. P. Cohen for taking the initiative to gather images from articles and online resources [2]. Finally to the Chest X-Ray Images (pneumonia) database in Kaggle for making a wonderful X-ray database for normal, viral and bacterial pneumonia images [3]. Also, a big thanks to our collaborators!

References: [1] S.I. S. o. M. a. I. Radiology. (2020). COVID-19 Database. Available: https://www.sirm.org/category/senza-categoria/covid-19/ [2] Joseph Paul Cohen and Paul Morrison and Lan Dao, "COVID-19 image data collection", arXiv:2003.11597, 2020 https://github.com/ieee8023/covid-chestxray-dataset. [3] P. Mooney. (2018). Chest X-Ray Images (Pneumonia). Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia