Covid19-Pneumonia-Normal Chest X-Ray Images

Published: 14 June 2022| Version 1 | DOI: 10.17632/dvntn9yhd2.1
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Description

- It is a medical images directory structure branched into 3 subfolders (COVID, NORMAL, PNEUMONIA) containing Chest X-ray (CXR) Images. - All images are preprocessed and resized to 256x256 in PNG format. - It helps the researcher and medical community to detect and classify COVID19 and Pneumonia from Chest X-Ray Images using Deep Learning. COVID-19: 1626 images NORMAL: 1802 images PNEUMONIA: 1800 images References: -If you are using this dataset for research purposes then cite the below articles: 1. Shastri, S., Kansal, I., Kumar, S. et al. CheXImageNet: a novel architecture for accurate classification of Covid-19 with chest x-ray digital images using deep convolutional neural networks. Health Technol. 12, 193–204 (2022). https://doi.org/10.1007/s12553-021-00630-x 2. Kumar S, Shastri S, Mahajan S, et al. LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images. Int J Imaging Syst Technol. 2022;1‐17. DOI: https://doi.org/10.1002/ima.22770

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Institutions

University of Jammu

Categories

Artificial Intelligence, Computer Vision, Machine Learning, Clustering, Image Database, Chest Imaging, X-Ray Imaging, Health, Image Classification, Classification System, X-Ray, Coronavirus, Convolutional Neural Network, Deep Learning, Image Analysis, COVID-19

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