Diagnosis of Pneumonia from Chest X-Ray Images using Deep Learning

Document Type : Original research papers

Authors

1 Computer and Control Engineering, Faculty of Engineering, Tanta University, Egypt

2 Computer and Control Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt

3 Faculty of Artificial Intelligence, Delta University for Science and Technology, Gamasa, Egypt

Abstract

Pneumonia is a disease of the lungs caused by a bacterial infection. Early diagnosis is critical to the outcome of treatment. In general, a trained radiologist may identify the condition using chest X-ray pictures. Diagnoses might be subjective for a variety of reasons, including the appearance of disease, which may be ambiguous in chest X ray pictures or mistaken with other conditions. As a result, computer-aided diagnostic systems are required to advise practitioners. In this study, we employed two well-known convolutional neural network models, Xception and VGG16, and a custom CNN model to diagnose pneumonia. We employed transfer learning and fine-tuning throughout the training step. The test findings indicated that the custom CNN model outperformed VGG16 network and the Xception model with 93% accuracy.

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Delta University Scientific Journal
Volume 7, Issue 3
Special Issue DU- IECRI 2024 Second International Engineering Conference on Research and Innovation Faculty of Engineering, Delta University, Egypt
November 2024
Pages 353-362

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