Information technology for early diagnosis of pneumonia on individual radiographs
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Дата
2020-12-01
Автори
Krak, Iurii
Barmak, Oleksander
Radiuk, Pavlo
Назва журналу
Номер ISSN
Назва тому
Видавець
CEUR-WS
Анотація
Nowadays, pneumonia remains a disease with one of the highest death rates around the world. The ailment’s pathogen instantly causes a large amount of fluid into the lungs, leading to acute exacerbation. Without preliminary examination and timely treatment, pneumonia can result in severe pulmonary complications. Consequently, early diagnosis of pneumonia becomes a decisive factor in treatment and monitoring the disease. Therefore, information systems that can identify early pneumonia on the Chest X-ray images are becoming more demanding nowadays. An individual approach to a person might be a promising way of early diagnosis. The presented study considers an approach to feature extraction of the early stage of pneumonia and identifying the disease using a relatively simple convolutional neural network. With only three convolutional and two linearization layers, the proposed architecture classifies radiographs with 90.87% accuracy, approaching the results of deep multilayer and resource-intensive architectures in classification accuracy and exceeding them in time efficiency. Our approach requires relatively fewer computing resources, confirming its efficiency in solving practical tasks on available computing devices.
Опис
http://ceur-ws.org/Vol-2753/paper3.pdf
Ключові слова
Convolutional neural network, pneumonia, early diagnosis, chest X-ray, radiograph, feature extraction, individual approach
Бібліографічний опис
Krak Iu., Barmak O., Radiuk P. Information technology for early diagnosis of pneumonia on individual radiographs // CEUR-Workshop Proceedings. 2020. Vol. 2753. P. 11-21.