Automated system of lung disease diagnosis on x-ray images
DOI:
https://doi.org/10.31548/energiya2022.01.060Abstract
Currently, automated detection of pneumonia in images is a priority in information technology. A promising option for solving this problem is the use of convolutional neural networks.
The purpose of the study is to develop an automated system for diagnosing pneumonia from X-rays.
This paper presents research and development of software for the automated system for analysis and classification of X-ray images of the lungs in order to automatically determine the signs of the disease, in particular pneumonia, which is most relevant due to the COVID-19 pandemic. This work is an example of the creation of a decision support system that is designed to assist a doctor to make decisions, analyze X-ray images of the lungs, classify them, and also allows to store all the necessary information about patients in one repository.
For the automated system software was developed using C# and the user interface development environment - WPF. During the implementation process there were used the MVVM architecture and ML.NET as a tool for the neural network setup.
Software was created based on the developed mathematical model through the integrated training of neural networks. To fulfill the main goal of software development, convolutional neural networks were used. As a result of the experiments, the coefficient of correctly recognized images was obtained – 97 %, which is close to the coefficient of recognition by a doctor.
Key words: disease recognition, image classification, neural network algorithms
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