A Convolutional Neural Network (CNN)-Based Pneumonia Detection Using Chest X-Ray Images

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Author(s): Jashasmita Pal (Odisha University of Technology and Research, Bhubaneswar, India)and Subhalaxmi Das (Odisha University of Technology and Research, Bhubaneswar, India)
Copyright: 2023
Pages: 20
Source title: Using Multimedia Systems, Tools, and Technologies for Smart Healthcare Services
Source Author(s)/Editor(s): Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-6684-5741-2.ch005

Keywords: Media & Communications / Medical Information Science Reference / Medical Technologies / Multimedia Technology

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Abstract

Pneumonia is a fatal illness; an infection that occurs in one or both human lungs. It is caused by either bacterial or viral infection. Pneumonia impacts mostly elders, as well as children under five. Thus, the early diagnosis of pneumonia can help the patient. So, an image classifier may help to diagnose patients with pneumonia in an automated and fast way. Chest X-rays (CXR) are frequently used to diagnose pneumonia and make many clinical decisions. Deep learning enhancements, especially impressive performances in picture categorization, have been demonstrated by convolutional neural networks (CNNs). In this chapter, the authors primarily concentrated on the capability of deep CNN, feature extraction approaches, and various machine learning classifiers for detecting pneumonia using X-ray image datasets. It also discusses various measures for calculating the performance of the model like accuracy, precision, recall, and f1 scores.

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A Convolutional Neural Network (CNN)-Based Pneumonia Detection Using Chest X-Ray Images

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