Asian Journal of Information Technology

Year: 2021
Volume: 20
Issue: 6
Page No. 168 - 173

COVID-19 Segmentation and Classification from CT Scan Images

Authors : Sridevi Ramachandra Rathod and Harmeet Kaur Khanuja

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.

How to cite this article:

Sridevi Ramachandra Rathod and Harmeet Kaur Khanuja, 2021. COVID-19 Segmentation and Classification from CT Scan Images. Asian Journal of Information Technology, 20: 168-173.

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