Sridevi  Ramachandra Rathod, Harmeet  Kaur Khanuja, 
    COVID-19 Segmentation and Classification from CT Scan Images,
    Asian Journal of Information Technology,
    Volume 20,Issue 6,
    2021,
    Pages 168-173,
    ISSN 1682-3915,
    ajit.2021.168.173,
    (https://makhillpublications.co/view-article.php?doi=ajit.2021.168.173)
    Abstract: The pandemic coronavirus disease-2019
(COVID-19) has infected millions of people in over 200
countries and territories as of 2021. It is very necessary to
detect COVID-19 in the initial stage to provide
appropriate medical treatment to patients and also to
protect the uninfected people. For this reason, we develop
a framework to automatically segment COVID-19 CT
images using k-means clustering and use them to train
proposed convolutional neural network to classify
COVID-19 from normal CT images. Rapid growth in
machine learning and deep learning has been doing great
work to reduce time of radiologists by assisting them in
the diagnosis of COVID-19. Our framework is evaluated
upon 349 positive and 397 negative CT scans to detect
COVID-19 and help in taking appropriate diagnostic
decisions. To evaluate the performance of proposed
approach, we compared our results with pre-trained
models such as VGG19, InceptionV3 and ResNet50.
    Keywords: COVID-19;segmentation;k-means;convolutional neural network;pneumonia