Path: Top -> Journal -> Telkomnika -> 2020 -> Vol 18, No 3, June
Classification of pneumonia from X-ray images using siamese convolutional network
By : Kennard Alcander Prayogo, Alethea Suryadibrata, Julio Christian Young, Telkomnika
Created : 2021-01-12, with 1 files
Keyword : chest x-ray, image classification, pneumonia, siamese convolutional network
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/14751
Document Source : Web
Pneumonia is one of the highest global causes of deaths especially for children under 5 years old. This happened mainly because of the difficulties in identifying the cause of pneumonia. As a result, the treatment given may not be suitable for each pneumonia case. Recent studies have used deep learning approaches to obtain better classification within the cause of pneumonia. In this research, we used siamese convolutional network (SCN) to classify chest x-ray pneumonia image into 3 classes, namely normal conditions, bacterial pneumonia, and viral pneumonia. Siamese convolutional network is a neural network architecture that learns similarity knowledge between pairs of image inputs based on the differences between its features. One of the important benefits of classifying data with SCN is the availability of comparable images that can be used as a reference when determining class. Using SCN, our best model achieved 80.03% accuracy, 79.59% f1 score, and an improved result reasoning by providing the comparable images.
Property | Value |
---|---|
Publisher ID | gdlhub |
Organization | Telkomnika |
Contact Name | Herti Yani, S.Kom |
Address | Jln. Jenderal Sudirman |
City | Jambi |
Region | Jambi |
Country | Indonesia |
Phone | 0741-35095 |
Fax | 0741-35093 |
Administrator E-mail | elibrarystikom@gmail.com |
CKO E-mail | elibrarystikom@gmail.com |
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