TY - GEN
T1 - COVID-19 Classification from CT-Scan Images Using Convolutional Neural Networks
AU - Baihaki, Rifki Ilham
AU - Sulistyaningrum, Dwi Ratna
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - COVID-19 is an epidemic that is currently global. This outbreak was first detected in Wuhan, China in December 2019. Since then this outbreak has claimed hundreds of lives. COVID-19 has similarities to Viral Pneumonia. So it becomes a challenge for researchers to create a method that is able to classify these two diseases. One of the uses of digital image processing is computed tomography (CT-Scan) imaging. Since its introduction in the medical clique in 1972, CT-Scan has grown to be used to image the human lung. The use of this imaging is to find out which part of the lung is affected by the disease. In this study, CT-Scans of normal lungs, COVID-19, and Viral Pneumonia will be classified using the Convolutional Neural Network (CNN). Based on the results of the study, it was found that the proposed method has a training accuracy of 100 percent. While the accuracy of the test is 95 percent.
AB - COVID-19 is an epidemic that is currently global. This outbreak was first detected in Wuhan, China in December 2019. Since then this outbreak has claimed hundreds of lives. COVID-19 has similarities to Viral Pneumonia. So it becomes a challenge for researchers to create a method that is able to classify these two diseases. One of the uses of digital image processing is computed tomography (CT-Scan) imaging. Since its introduction in the medical clique in 1972, CT-Scan has grown to be used to image the human lung. The use of this imaging is to find out which part of the lung is affected by the disease. In this study, CT-Scans of normal lungs, COVID-19, and Viral Pneumonia will be classified using the Convolutional Neural Network (CNN). Based on the results of the study, it was found that the proposed method has a training accuracy of 100 percent. While the accuracy of the test is 95 percent.
KW - COVID-19
KW - Convolutional neural network
KW - Image classification
UR - http://www.scopus.com/inward/record.url?scp=85128227123&partnerID=8YFLogxK
U2 - 10.1109/ISMODE53584.2022.9742807
DO - 10.1109/ISMODE53584.2022.9742807
M3 - Conference contribution
AN - SCOPUS:85128227123
T3 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
SP - 75
EP - 79
BT - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
Y2 - 29 January 2022
ER -
